New Delhi [India], October 2: Managed vector databases have become considerably easier to try without paying for infrastructure upfront. What began as short trials and limited development sandboxes has evolved into a market where several established providers now offer persistent free cloud tiers suitable for prototypes, semantic search projects, RAG systems and small AI applications.
The limits differ substantially. Some providers emphasize storage capacity, others provide generous read and write allowances, while a growing number are adding inference and higher-level AI services around the database itself.
Here are five notable managed cloud vector database options with ongoing free access as of October 2026.
Weaviate introduced an always-free managed cloud tier in June 2026, extending the company’s existing open-source model into Weaviate Cloud.
The free plan includes one managed cluster per user with up to 100,000 objects, 1 GB of memory, 10 GB of disk, one collection and as many as three tenants. No credit card is required and the cluster does not have a fixed trial expiration.
The database includes the core retrieval capabilities developers would expect from Weaviate, including vector search and hybrid search, which combines semantic vector retrieval with lexical BM25 search. Developers can therefore test search architectures that require more than straightforward nearest-neighbor retrieval.
Where the free offering becomes particularly useful for AI application development is in the surrounding services.
Weaviate includes up to 2,000 hosted embedding requests per day, allowing applications to generate embeddings through Weaviate rather than necessarily integrating a separate inference provider. The free tier also includes 1,000 Query Agent requests per month.
Query Agent lets applications query data using natural language. It can determine which data to search, construct filters and sorts, choose retrieval strategies and perform aggregations. The current free allowance translates to as many as 1,000 Search-mode queries or 250 Ask-mode queries per month because Ask consumes four request units.
Weaviate also makes Engram available through a free tier. Engram is a memory server for AI agents and applications that extracts, transforms and stores useful memories rather than simply preserving raw conversation histories. Its pipeline can reconcile new information with existing context, including merging, consolidating and resolving conflicting memories before committing changes.
That gives developers several pieces of an AI application stack within the same platform: the managed database, embeddings, hybrid retrieval, natural-language database interaction and persistent agent memory.
Weaviate remains open source as well, so developers who eventually want to manage their own infrastructure retain a self-hosting path outside Weaviate Cloud.
The free managed cluster is designed primarily for exploration and prototypes rather than highly available production workloads, but it provides enough capacity and surrounding services to build substantial working applications before moving to a paid deployment.
Pinecone’s Starter plan gives developers permanent access to its fully managed vector infrastructure without requiring a paid subscription.
The current free allowance includes up to 2 GB of database storage, five indexes, 100 namespaces per index, 2 million write units per month, 1 million read units per month and 1 GB of monthly egress.
Pinecone estimates that 2 GB can hold roughly 300,000 records when using 1,536-dimensional vectors and approximately 500 bytes of metadata per record, although actual capacity depends on the data being stored.
The platform supports dense, sparse and full-text indexes, giving developers multiple approaches to retrieval without leaving the managed service. That makes the free plan applicable to conventional semantic search as well as workloads that combine lexical and semantic techniques.
Pinecone also extends beyond the database through Pinecone Inference. Its Starter plan provides access to embedding models and limited reranking, allowing developers to handle part of the retrieval pipeline within Pinecone rather than building every component around external inference providers.
Another part of the free offering is Pinecone Assistant. The Starter tier currently includes 1 GB of Assistant storage together with allowances for input, output, context-processing and ingestion usage. Assistant is designed for applications that need to answer questions from stored documents without manually building every element of a RAG pipeline.
Pinecone’s free tier therefore covers considerably more than vector storage. Developers can experiment with multiple retrieval types, managed inference, reranking and higher-level document-question-answering functionality while staying within one cloud service.
Unlike Weaviate, Milvus and Qdrant, Pinecone does not provide an open-source version of its core managed database for self-hosting. Its model remains centered on operating vector infrastructure as a cloud service.
For developers who prefer that fully managed approach, the Starter plan provides enough database and AI-service capacity for meaningful experimentation and smaller applications.
Milvus is an open-source vector database, while Zilliz Cloud provides its closely associated managed cloud experience.
Zilliz offers one free cluster per organization with 5 GB of storage, up to five collections and 2.5 million virtual compute units, or vCUs, each month. No payment information is required to create the free cluster.
Zilliz estimates that the 5 GB capacity is sufficient for approximately one million 768-dimensional vectors. The precise number depends on vector dimensions, metadata and index configuration, but the published estimate illustrates the amount of data developers can work with on the free plan.
Rather than imposing a simple query-count allowance, Zilliz measures read and write consumption using vCUs. Operations including search, query, insert, upsert and delete consume this monthly allocation.
That model gives developers room to test different usage patterns while working with the same Milvus technology used for substantially larger vector deployments.
Milvus itself has developed around high-scale similarity search and supports features including filtering, multiple index strategies and hybrid retrieval patterns. Using Zilliz Cloud removes the operational work of provisioning and maintaining a Milvus deployment while retaining access to its broader ecosystem.
The free tier concentrates primarily on the database and its retrieval capabilities rather than bundling a large collection of agent-oriented services around it.
That can be useful for developers who specifically want to evaluate vector database architecture, indexing and retrieval at meaningful data volumes without introducing additional layers into the stack.
Because Milvus remains open source, projects can also move between managed Zilliz infrastructure and independently operated Milvus deployments depending on their future infrastructure requirements.
Qdrant combines its open-source vector database with a managed cloud service that includes a permanent free cluster.
The free cluster consists of a single node with 0.5 vCPU, 1 GB of RAM and 4 GB of disk. Qdrant describes the tier as free forever and positions it for testing and prototypes.
The resource-based model differs from services that specify a fixed number of vectors. The number of records that fit into the cluster depends on vector dimensions, metadata payloads, indexing configuration and techniques such as quantization.
This gives developers direct control over how they use the available memory and storage rather than tying the plan to one standardized vector count.
Qdrant has particularly extensive support for payload filtering, allowing structured metadata conditions to participate directly in vector retrieval. Applications can combine semantic similarity with attributes such as category, timestamp, location or user-specific properties without separating those operations into independent systems.
Qdrant Cloud also includes free inference with selected models on the free tier.
This allows developers to experiment with embedding and vector-search workflows without necessarily operating their own inference infrastructure for every use case.
Like Weaviate and Milvus, Qdrant also maintains an open-source version of its database. Projects can therefore begin on a managed free cluster while preserving the option to deploy Qdrant independently later.
The free cluster does not include high availability, backup and disaster-recovery capabilities or the service-level commitments available on paid plans. Those limitations are consistent with its positioning as a development and prototype environment rather than production infrastructure.
For developers who want a managed environment while retaining relatively direct control over vector database behavior, the free Qdrant Cloud cluster provides a substantial testing ground.
Upstash Vector approaches the category from a serverless perspective rather than exposing a traditional continuously provisioned vector database cluster.
Its free plan includes one vector database, a maximum capacity of 200 million vector dimensions, up to 100 namespaces and as much as 1 GB of associated data and metadata.
The service allows up to 1,536 dimensions per vector on the free plan.
Because Upstash expresses storage capacity as total vector dimensions, the practical number of records depends directly on embedding size. At 768 dimensions, 200 million dimensions theoretically correspond to roughly 260,000 vectors. At 1,536 dimensions, the equivalent is approximately 130,000 vectors before considering the other limits of the database.
The free tier also provides 10,000 queries and 10,000 updates per day.
Those recurring daily allowances make the service useful for applications that need consistent activity rather than an environment used only occasionally for development.
Upstash Vector supports namespaces, metadata filtering and live index updates, allowing applications to segment data and combine semantic retrieval with structured conditions. Developers can access the service through REST as well as Python, TypeScript and Go SDKs.
Its serverless architecture means developers do not need to size or maintain a vector database cluster. The application interacts with the service while Upstash handles the underlying infrastructure.
The free plan focuses closely on vector retrieval rather than providing the broader agent and memory layers offered by some other platforms, but its substantial daily request limits make it practical for semantic search, recommendations and lightweight RAG applications.
The important shift in 2026 is not simply that developers can store vectors for free. The free offerings now reflect several different approaches to building AI infrastructure.
Weaviate provides a managed vector database alongside hosted embeddings, Query Agent and Engram memory. Pinecone combines vector infrastructure with inference, reranking and Assistant. Zilliz gives developers substantial managed Milvus capacity measured through storage and compute usage. Qdrant combines an open-source database with a resource-based managed cluster and selected free inference. Upstash provides a serverless model with recurring daily query and update allowances.
The differences become useful because vector applications themselves are becoming more varied.
A semantic-search application may value storage and high query allowances. A RAG system may benefit from integrated embedding or reranking services. An agentic application may need retrieval plus persistent memory. A development team expecting eventually to operate its own infrastructure may also care whether the underlying database remains available as open-source software.
Free managed vector databases have consequently moved well beyond disposable demonstrations. Their current allowances are large enough to build functioning applications, evaluate architectures with real data and determine which parts of an AI stack developers want the database platform itself to handle.
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RAI ReTechCon2026_LtoR_Kumar Rajagopalan – CEO of RAI, Rajesh Jain – MD & CEO, Lacoste India, and Sanjay Vakharia – CEO, Spykar Lifestyles
Mumbai (Maharashtra) [India], September 29: The Retailers Association of India (RAI) successfully hosted the 20th edition of the Retail Technology Conclave, ReTechCon 2026, on September 23–24 at JW Marriott Mumbai Sahar. As India’s premier retail technology forum, the event brought together CEOs, CIOs, technology partners, and industry leaders to explore how intelligence, automation, and unified commerce are transforming retail, while driving smarter decision-making, seamless customer experiences, and a more connected, future-ready retail ecosystem.
ReTechCon 2026 offered an immersive experience that brought together the depth of expert-led discussions with the scale and diversity of a premier industry conclave. Participants gained valuable insights into emerging technologies, evolving global trends, and innovative solutions shaping the future of retail, with a focus on driving smarter, more connected, and future-ready businesses.
Speaking about ReTechCon 2026, Kumar Rajagopalan, CEO, Retailers Association of India (RAI), said, “Retail has spent 50years organising itself around five Ps — people, product, place, promotion, price. Technology has quietly added two more: pace and personalisation. AI is no longer a pilot project sitting in some retailers’ innovation labs — it is already reshaping how customers are found, how products are tracked, and how every transaction becomes a data point. ReTechCon 2026 exists to have that conversation honestly, not as a sales pitch, but as an industry working out together what comes next.”
Saloni Khosla, Vice President, Pepperfry:
“In a category like furniture, technology has to solve for a very specific problem — the customer can’t just add it to cart the way they would a t-shirt. They need to see it in their space, trust the delivery timeline, trust the return process if it doesn’t fit. Adoption for us has never been about chasing whatever’s trending. It’s been about asking which technology actually removes hesitation at the exact moment the customer is deciding, and ignoring the rest.”
Chirag Kenia, Founder, Urban Platter:
“Every retailer today has access to roughly the same technology. What separates the ones who actually benefit from it is whether they’ve rebuilt their processes around it, or just bolted it onto the old way of doing things. We learned that the hard way — buying a tool is the easy part. Changing how your team actually works with it is where most of the value gets lost or won.”
Karan Singla, COO, The Sleep Company:
“The retailers who are winning right now aren’t the ones with the most advanced stack. They’re the ones who adopted early enough to make mistakes while the stakes were still small. Waiting for a technology to mature before you touch it sounds prudent, but by the time it’s ‘mature,’ your competitor has three years of data and muscle memory you don’t have.”
At ReTechCon 2026, distinguished speakers shared their invaluable insights, enriching the discussions with diverse perspectives on retail technology.
Other notable speakers at ReTechCon 2026 included leading retail and technology experts such as Anil Menon, CIO, LuLu Group India; Neeraj Nagpal, CBO, Raymond; Chippy Mehta, Co-Founder, Bombay Shirt Company; Kunal Mehta, CIO, Arvind Fashions Ltd.; Chirag Kenia, Founder, Urban Platter; Vinod Kapote, Head – IT, Trent Ltd.; and Ranjit Satyanath, Chief Information Officer, Vijay Sales.
Discussions at ReTechCon 2026 explored the key trends and technological developments reshaping the retail landscape, offering valuable perspectives on the evolving industry and emerging opportunities. Key topics of discussion included:
About ReTechCon
ReTechCon stands as the sole knowledge dissemination platform concentrating on the technological aspects of the retail sector. Incepted 12 years ago, the platform has flourished to become India’s largest gathering of CIOs/CTOs, technology service providers, and mavens in the retail technology sphere. Its mission is to guide retailers in keeping pace with the swift technological transitions and adapting for their enterprises’ and customers’ advantage. Visit www.retechcon.com for more information.
The Retailers Association of India is the national body representing India’s retail industry across all channels and formats, from large format and specialty retail to e-commerce, quick commerce, and connected commerce businesses. RAI works with governments, regulators, and industry stakeholders to enable a competitive, innovation-friendly retail ecosystem. Through policy advocacy, industry events, research, and learning programmes, RAI builds the conditions for retail to grow, invest, and create employment at scale. India’s retail future is connected. RAI is building for it.
Visit: www.rai.net.in | Follow on Twitter: @rai_india
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]]>Mumbai (Maharashtra) [India], September 23: Think about the manager who talks a stressed-out employee off the ledge on Monday morning (read someone threatening to have a breakdown and resign), sits through a budget fight with another department on Tuesday, and then has to explain a confusing new policy from leadership to new hires in the their team on Wednesday – all before lunch on Thursday. That’s a fairly normal week for a middle manager.
They’re not the ones setting the big vision. They’re not the ones doing the hands-on work either. They’re the people in between, and honestly, they’re some of the hardest-working, least-appreciated people in any company.
Middle managers get hit from all sides, all the time. They have to absorb shocks and continue to deliver.
From above, there’s pressure to hit targets, roll out new initiatives, and make sense of decisions they often didn’t have a hand in making. From the side, there’s friction – other teams pulling on the same resources, chasing different priorities, or simply not talking to each other. Collaboration. Silos. Inter-dependence is a daily focus for the Middle Manager. And from below, there are people who need coaching, encouragement, someone to fight for them, and someone to steady them when things go wrong.
That’s not one job. That’s three jobs, wearing one name tag. No wonder it’s exhausting.
Here’s the strange part: companies spend a lot of time and money developing their senior leaders. They spend a lot of time and money training their frontline teams. But the folks stuck in the middle, doing arguably the trickiest job of all? They mostly get left to figure it out on their own.
Leadership programs are usually written with executives in mind.. people setting strategy and vision. Skills programs are written for people doing a specific, definable job. Middle managers don’t fit into either box. Their job isn’t about strategy or a single skill; it’s about people, translation, and constant compromise. So when it comes time to build training, they slip through the cracks.
They end up learning the hard way, through trial, error, and a lot of quiet frustration.
When middle managers don’t get support, it doesn’t stay their problem for long.
Big ideas from leadership lose their shine somewhere on the way down if the manager passing them along doesn’t know how to make them make sense. Teams start to feel the strain, because for most employees, their manager is the company – how that person shows up shapes everything about how work feels. And when managers get worn down, they leave, and they take a lot of hard-won knowledge and team trust out the door with them.
The middle isn’t just a layer on an org chart. It’s the glue. Neglect it, and things everywhere else start to come loose.
Supporting middle managers well isn’t about handing them a slide deck from an executive course or a shrunk-down version of frontline training. It means starting from what they actually deal with every day:
This is one of the things Tutul Consulting spends time on: Urging leaders to involve the overlooked middle layer in transformation, in decisions, in culture shaping. All our OD interventions include the top and senior middle management.
Middle managers keep organizations standing, often quietly, often without much thanks. They deserve more than whatever’s left over once the top and bottom of the chart have been taken care of. That’s where Tutul Consulting bridges the distance because when the unsung heroes in the middle are supported , everyone around them feels it too.
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]]>HAR is being designed to help real people voluntarily participate in AI projects, verify consent through selective disclosure, and earn from eligible contributions while supporting authentic human-origin data for AI development.
Mumbai (Maharashtra) [India], September 19: MotionGravity is developing the Human Authenticity Registry (HAR), a human-verification and contributor framework intended to give ordinary people a legitimate way to participate in the growing AI economy through consent-based, paid contribution.
As artificial intelligence becomes part of everyday life, most people experience AI as users or consumers. HAR is being developed around a different idea: people should also be able to participate directly in how AI systems are improved, understand what they contribute, give clear consent, and receive value.
At its core, HAR is intended to establish that a real human participated in a contribution or provided consent, while supporting selective disclosure so people do not necessarily need to expose more personal information than required for a specific purpose.
The aim is to create a trusted layer between people and AI projects: one where human participation can be verified, consent recorded clearly, and contributors can benefit from that verification.
“AI is being built from human knowledge, behaviour, language, images, voices and real-world experience, but ordinary people rarely have a direct way to participate in that process,” said Jythesh T Achary, Technical Director at MotionGravity. “HAR is being developed to create that pathway — where a real person can knowingly consent, contribute something of value, and be paid for eligible participation. At the same time, projects gain greater confidence that the data they receive comes from authentic human participants.”
Rather than treating contributors as anonymous one-time sources of data, HAR is intended to create continuity. Once verified, a person may become eligible for projects based on language, location, skills, knowledge, devices, documents, or other requirements.
Verification is therefore intended to become more than a security check. A verified participant may be able to access future opportunities where authentic human participation matters, while avoiding the need to repeatedly establish that they are a real consenting person.
MotionGravity is developing specialised contributor projects on top of this HAR verification layer.
Project Atlas focuses on authentic documents and document imagery. Contributors can check whether documents they already possess may be eligible for a current requirement by identifying the document name or type. No upload is required simply to check eligibility.
Where a project requires genuine real-world documents from consenting individuals, HAR verification can provide additional confidence around the human source and participation behind that data. For contributors, Atlas creates a way to discover whether documents they legitimately possess may qualify for a paid contribution.
Project Lumen applies the same principle to human knowledge and video. Verified contributors may participate by explaining, teaching or demonstrating subjects and skills they genuinely know.
That may include a practical activity, software workflow, professional subject, trade, hobby, lesson, equipment demonstration, interview or presentation. The objective is not to recruit influencers or professional presenters, but to enable ordinary people to contribute authentic human knowledge in a form that can help improve AI systems.
Together, Atlas and Lumen demonstrate how HAR can move from verification into practical participation: one trusted human layer supporting different forms of authentic data contribution.
MotionGravity’s broader objective is to make AI participation accessible beyond traditional technology and data-work roles.
A person may qualify for one project because of a language they speak, another because of a skill they can demonstrate, another because of a document they possess, and another because of their voice, image or real-world experience.
In this model, people are not simply treated as raw sources of data. They become recognised participants in the process. MotionGravity describes the goal as creating a legitimate pathway through which individuals can consent, contribute and earn, while helping AI systems gain access to authentic human-origin data.
HAR is also being developed with longer-term applications around digital authenticity. As synthetic images, voices and videos become more sophisticated, MotionGravity intends to explore how the verification layer can eventually support broader anti-deepfake, authenticity and consent-verification technologies.
The company plans to expand HAR with additional opportunities across image, speech, audio, language, video, documents and other multimodal data categories.
MotionGravity is an India-based technology and data services organisation specialising in precision data collection and AI dataset production. Its capabilities include audio and speech data, transcription, annotation, OCR, image and video collection, dubbing, captioning, language services and multimodal data programs.
Through HAR and contributor projects such as Atlas and Lumen, MotionGravity is developing infrastructure intended to connect verified human participation with legitimate AI-data requirements.
Email: connect@motiongravity.in
Learn more / Join the HAR Contributor Network: https://join.harregistry.org/contributor-signup
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]]>The recognition comes at a pivotal time. According to the latest NASSCOM–Zinnov India GCC Landscape Report, India is now home to over 2,100 Global Capability Centres, employing more than 2.3 million professionals and generating close to $100 billion in revenue – making it the world’s largest GCC ecosystem. Many of these centres are standardising on Apple devices to support engineering, R&D, and innovation-led teams that expect enterprise-grade security alongside a best-in-class user experience. Team Computers has positioned itself as a partner of choice for these organisations, helping them modernise their digital workplace, streamline device lifecycle management, and align global technology standards with local execution.
“This recognition from Apple is a strong validation of the trust enterprises place in us to build their digital workplace. As we work towards our $1 billion vision, our focus remains on going deeper into segments like GCCs, where the demand for secure, high-performing device ecosystems is only growing. Being India’s top Apple partner is a reflection of the discipline and customer-first approach that has shaped our growth for nearly four decades,” said Nizam Siddiqui, Apple Practice Head, Team Computers.
As GCCs and large enterprises expand their footprint in India, the demand for secure, seamless, and scalable device ecosystems has never been greater. Team Computers works closely with organisations across industries to deploy Apple solutions that improve collaboration, strengthen security, and deliver an exceptional user experience at scale – combining deep technical expertise with end-to-end consulting, deployment, and support capabilities to simplify IT management and optimise total cost of ownership.
In addition to its Tier 1 Apple Premium Business Partner status, Team Computers is also an Apple Authorised Service Provider (AASP), enabling customers to benefit from comprehensive lifecycle support under one roof. From procurement and deployment to device management, maintenance, repair, and refresh, the company provides end-to-end services that maximise the value of enterprise Apple investments – a capability increasingly critical for GCCs and enterprises managing large, distributed device fleets.
This recognition is one of several markers of Team Computers‘ broader growth strategy, as the company continues to invest in its enterprise offerings – spanning digital workplace, cybersecurity, cloud, managed services, AI analytics, and business applications – to support India’s fastest-growing business segments.
With nearly four decades of experience delivering enterprise IT transformation, Team Computers continues to empower businesses – from global capability centres to large domestic enterprises – with future-ready workplace solutions that combine world-class technology, operational excellence, and customer-centric service.
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]]>Questions Around Technology, Pricing, and Product Specifications Highlight the Importance of Clear Information for Home Elevator Buyers
New Delhi [India], September 16: For homeowners investing ₹10 lakh or more in a premium home elevator, the technology installed inside the shaft is an important part of the purchase. It can influence expectations around performance, engineering, maintenance, safety, serviceability and price. This is why questions can arise around how Odyssey Elevators describes the technology used in its home elevators, particularly when prospective customers may interpret an electric-drive description as referring to a specific lifting arrangement such as traction, while other information may point to a drum-winding configuration.
The issue is therefore less about using one term or another and more about whether customers receive clear and technically specific information before making a high-value purchase. If the mechanism supplied differs from what a buyer understood from the product description, the distinction becomes relevant to informed consumer choice.
The fact that a home lift operates using electricity does not, by itself, define the lifting technology. Electrical power is the energy source used to operate the system; it does not explain the mechanism that actually moves the elevator car. The relevant technical question is how the car is lifted and controlled—for example, through a traction arrangement or through a drum-winding mechanism. Different lifting mechanisms can involve different engineering configurations, specifications and performance characteristics.
The source material reviewed for this article notes that Odyssey publicly positions its offering around “Premium Electric Circular Home Elevators” and advanced electric-drive technology. It also notes similar electric-drive positioning by Brio Elevators for its circular lift. For prospective buyers, the practical question is simply: what specific drive and lifting mechanism are included in the elevator being quoted, manufactured and installed?
A more detailed sales process can make this easier to understand by identifying the mechanism in technical terms rather than relying only on broad marketing descriptions. Customers should be able to understand the specification and scope of the product before signing a contract or making a substantial advance payment.
The technology discussion is also relevant to pricing. The source material refers to market discussions and customer questions about the relative equipment costs of drum-winding configurations, alongside reported prices of approximately ₹10 lakh to ₹17 lakh for certain premium home elevators.
These figures should not, on their own, be interpreted as evidence that a particular elevator has been incorrectly priced. The final price of a premium elevator can include design, cabin construction, customization, installation, civil work, controls, safety equipment, after-sales service, warranties and other components. At the same time, when a customer is paying a significant amount, a clear description of the underlying technology can help explain what is included in the quoted price.
For buyers, the useful question is straightforward: does the quoted price correspond to the complete engineering specification and package being supplied? Clear documentation can help customers make that comparison without relying solely on marketing terminology.
It is important to distinguish the technology itself from the question of disclosure. A drum-winding home lift can be a legitimate lifting technology when appropriately designed, manufactured, installed and maintained. The discussion in the source material is therefore not that drum winding is inherently unsafe or unsuitable.
The more useful distinction for a buyer is between describing a product broadly as an “electric lift” and specifying whether the lifting mechanism is traction-based or drum-winding, with an electric motor providing the power. For a technically significant purchase, that information is most useful when it is available before installation and clearly reflected in the quotation or technical documentation.
The source material also discusses the corporate relationship between Odyssey Elevators and Brio Elevators. Public corporate-information records cited in the original document identify Venkatesh Jagabathina and Afash Mahammad Shaik as designated partners of Brio Elevators LLP and also as directors of Odyssey Elevators Private Limited. Odyssey’s own website is cited as identifying Venkatesh Jagabathina as founder and CEO of both businesses.
These corporate connections do not, by themselves, indicate wrongdoing or establish that the businesses have acted improperly. However, clear identification of the relevant business entity can be useful for customers, particularly where related businesses offer products with similar descriptions. Buyers may reasonably want to know which entity is responsible for the quotation, manufacturing, installation, warranty and after-sales service associated with their purchase.
For a high-value home elevator, buyers should request a written technical specification before making payment. The document should identify the drive mechanism, motor arrangement, winding method, controller, safety systems and major components, along with the applicable warranty and service terms.
If Odyssey’s elevators use a traction-based system, the company can address questions about the technology by providing the relevant technical specifications and explaining how the installed mechanism operates. If a particular model uses drum winding, that can likewise be stated clearly in the quotation and technical documentation. This approach gives customers a concrete basis for comparing different products.
Ultimately, the most useful approach is transparency. Customers should be able to compare home elevators on engineering specifications, safety provisions, service commitments and total value—not simply on premium terminology. Clear technical disclosure can help prospective buyers understand what they are purchasing and can also give manufacturers an opportunity to explain their technology accurately and directly.
*This article is based on the supplied source document. References to customer questions, market discussions and technical or corporate matters are presented for informational purposes and are not stated as independently established findings. The article does not make a determination of wrongdoing by any company or individual.
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]]>The new offering moves audits from sample-based checks to 100% transaction verification, extending Valiance’s multimodal intelligence engine into enterprise audit and compliance workflows.
Noida (Uttar Pradesh) [India], September 15: Valiance Solutions, a provider of applied AI solutions for enterprise and public-sector clients, today announced the launch of Audit AI, a new AI-led audit automation point solution built on top of its multimodal AI platform.
Audit AI is designed to help audit and compliance teams move beyond manual, sample-based reviews toward complete, intelligence-driven verification of every transaction and voucher.
Traditional audits remain constrained by manual voucher checks, limited sampling, and fragmented records. As transaction volumes grow, auditors are often forced to trade depth for speed—a gap that leads to missed anomalies, delayed closures, and compliance leakage. Audit AI addresses this by automating verification, flagging anomalies, and surfacing hidden risk patterns across the full body of audit records, rather than a sampled subset.
At its core, Audit AI runs on Valiance’s multimodal AI platform, built to ingest and fuse data across formats—scanned vouchers, PDFs, invoices, spreadsheets, and structured transaction records—into a single, unified layer of audit intelligence. Rather than treating each document type as a separate problem, the platform reads across formats and sources simultaneously, giving auditors one consistent, evidence-linked view of every transaction instead of siloed, format-by-format checks.
“Audits today are still built for a smaller, slower era of paper trails and manual sampling,” said Shailendra Singh Kathait, CTO & co-founder at Valiance Solutions. “Audit AI changes that. It gives auditors 100% verification with full explainability, so teams get faster audits and stronger governance without giving up control of the final decision.”
Audit AI follows a four-step workflow purpose-built for audit teams:
Throughout the process, human auditors remain in control of approvals, escalations, and final decisions—AI accelerates detection and coverage; it does not replace auditor judgment.
Audit AI is the newest point solution to be built on Valiance’s multimodal AI platform—the company’s enterprise AI engine for turning fragmented evidence and institutional knowledge into investigation-ready, decision-ready intelligence. This platform already powers specialized intelligence suites for technical/investigative analysis and financial crime investigation, each built on the same underlying multimodal capabilities: ingestion across text, documents, images, video, and structured data; automated entity extraction; knowledge-graph correlation; and natural-language query across an entire evidence corpus.
By extending this same multimodal foundation into the audit function, Audit AI inherits the platform’s core intelligence layer—the ability to fuse and reason across mixed data formats—while applying it to a distinct, high-volume use case: routine financial and compliance audits. It is packaged as a focused, ready-to-deploy solution for audit and finance teams so that the same platform intelligence used for complex investigations can now verify everyday vouchers and transactions at scale. Organizations already using Valiance’s platform for investigations or institutional knowledge can adopt Audit AI as a natural, multimodal extension of the same platform rather than a separate, disconnected tool.
● 100% Verification—Every voucher is checked, not just a sampled subset.
● AI Pattern Detection—Identifies repeat claims, anomalies, and behavioral risk signals across records.
● Explainable Findings—Every flag is backed by clear logic and evidence, supporting audit defensibility.
● Policy-Aware Intelligence—Audit rules and thresholds are embedded directly into workflows.
● Auditor in Control—Human approvals and escalations remain central to every decision.
● Audit-Ready Outputs—Instant reports, logs, and traceable digital audit trails.
● Scalable Design—Built to handle thousands of records across departments without added audit effort.
Audit AI is available now for enterprise and public-sector organizations, with deployment options built around each client’s security and infrastructure requirements:
Interested teams can book a demo directly through Valiance Solutions to see the platform applied to their own audit workflows and discuss which deployment model best fits their environment.
Valiance Solutions is a deep-tech AI company, built by Indians in India, for India and beyond, on a mission to build sovereign, world-class AI platforms for enterprise, government, and defense institutions. Rather than assembling point tools, Valiance has invested years in fundamental research to build its own multimodal AI platform from the ground up—one capable of ingesting and reasoning across text, documents, images, video, audio, and structured data as a single, unified layer of intelligence.
This same platform powers dual-use AI applications across both civilian and strategic domains: from wildlife conservation and urban public safety to procurement and audit intelligence to mission-critical deployments for government and defense institutions. It is this multimodal, dual-use foundation—built for high-security, sovereign environments—that underpins Valiance’s full product portfolio, including Knowledge Miner, Audit AI, CivicEye, Citizen Assist, Tender Evaluation, Guard Vision AI, and Wildlife EYE & IQ, deployed across industrial, retail, and government environments, including sovereign, air-gapped deployments for high-security clients.
For more information, visit valiancesolutions.com.
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]]>The partnership brings global investing to Wizzmoni’s customers through a simple, digital experience powered by Appreciate’s GIFT City IFSC infrastructure
Mumbai (Maharashtra) [India], September 10: Wizzmoni Financial Services Limited (formerly Unimoni Financial Services Limited), one of India’s leading foreign exchange and financial services providers, today announced a strategic partnership with Appreciate, a global investing infrastructure platform, to enable its customers to invest in global markets seamlessly through the Wizz Financial App.
Through the partnership, Wizzmoni will integrate Appreciate’s global investing infrastructure through an SDK, enabling retail and HNI customers to access US-listed stocks and Global Mutual Funds directly through the Wizz Financial App. The integration expands Wizzmoni’s financial services offering to include global investing, allowing customers to access global markets alongside its existing international payments and foreign exchange services.
The Wizz Financial App brings together Wizzmoni’s digital financial services, offering customers a single platform for managing their cross-border financial needs. With the addition of global investing, customers can access investment opportunities alongside services such as foreign exchange, international money transfers, travel and digital payments, creating a more connected digital experience.
The solution is built on Appreciate’s regulated GIFT City IFSC infrastructure, providing customers with a compliant route to international investing. Customers will be able to access US stocks with fractional investing from $1 and Global Mutual Funds from as low as $100, making global investments accessible across a wider range of investment sizes.
The partnership builds on Wizzmoni’s long-standing expertise in foreign exchange, international money movement and financial services. Wizzmoni currently serves customers through its nationwide network and digital channels, and is part of Wizz Financial, a global platform for payments and foreign exchange solutions.
For Wizzmoni, the partnership represents an expansion from facilitating cross-border money movement to enabling cross-border investing, giving customers a new way to deploy their international financial flows into global assets.
Amir Nagammy, Founder & CEO, Wizz Financial said: “Our vision at Wizz Financial has always been to empower our customers by breaking down complex financial barriers. Partnering with Appreciate marks a pivotal step in expanding the Wizzmoni’s ecosystem from cross-border remittances into true global wealth creation. By combining our deep trust, extensive physical footprint, and digital outreach with Appreciate’s robust investment infrastructure, we are making global diversification simple, transparent, and accessible for every Indian resident—no matter where they are located.”
C A Krishnan R, Director & CEO, Wizzmoni said: “With Indian retail investors & HNI customers increasingly looking to diversify their portfolios into global assets, offering a compliant and friction-free path under the RBI’s LRS framework is essential. Through this strategic tie-up, Wizzmoni combines digital speed with hands-on branch support. Whether our clients prefer a 100% self-serve digital experience on the app or hands-on guidance from our relationship managers in-branch, we are providing a secure, compliant, and frictionless pathway to global markets.”
Subho Moulik, Founder & CEO, Appreciate, said: “We believe that global investing should be as seamless as moving money across borders. Wizzmoni already has a strong relationship with customers through its foreign exchange and international financial services, making it a natural partner to take global investing to a much wider audience. Through this integration, we are bringing US stock investing into Wizzmoni’s existing digital journey, powered by our regulated GIFT City infrastructure.”
The partnership reflects the growing convergence between cross-border payments, foreign exchange and global investing, as Indian customers increasingly seek access to international markets and global investment opportunities.
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]]>Ahmedabad (Gujarat) [India], September 9: Ganesh Chaturthi has evolved into one of India’s most social festivals, with people sharing everything from pandal visits and home decorations to aarti moments, family gatherings and festive greetings across social media platforms. Today, celebrations are not just experienced in person but are also captured, created and shared digitally.
Driven by its customer-first approach, Airtel continues to go beyond delivering a best-in-class network experience by bringing digital benefits that help customers stay connected, express themselves creatively and share what matters most.
This festive season, Airtel customers can add a creative edge to their social media celebrations with Adobe Express Premium. Customers who have not yet claimed their benefit can still activate their Adobe Express Premium access until January 2027.
With access to premium templates, AI-powered creative tools, images, fonts and design assets, customers can quickly create festive content that stands out across Instagram, Facebook, WhatsApp and other social platforms.
This Ganesh Chaturthi, customers can:
As customers increasingly use social media to celebrate and connect, Adobe Express Premium enables them to create content that is more personal, engaging and reflective of their unique celebrations.
The collaboration reflects Airtel’s broader commitment to enriching customer experiences beyond connectivity by combining a best-in-class network with innovative digital partnerships. Together, Airtel and Adobe are empowering customers to create, share and celebrate every festive moment with greater creativity and impact
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]]>Within two months of deployment, the AI agents achieved an 88% automated resolution rate across selected support queries while reducing average handle time by approximately 30%
Bengaluru (Karnataka) [India], September 8: Arrowhead, a Bengaluru-based enterprise voice AI company, has announced results from its deployment with digital lending platform Kissht. Within two months of launch, Arrowhead’s AI voice agents began handling 40% of all inbound customer support calls received through Kissht’s Ring app.
The deployment currently covers loan application rejection queries and requests related to mandate or No Objection Certificate cancellations. Approximately 88% of these calls are resolved without human intervention.
“Within the first two months, the bot was handling 40% of our entire inbound volume,” said Suraj Shetty, Head of Customer Experience, Learning and Development at Kissht (Ring). “Of those calls, around 88% are getting handled without needing a human at all.”
Unlike many voice AI deployments that begin with outbound sales or engagement use cases, Arrowhead and Kissht introduced the technology directly into inbound customer support. The initial deployment focused on queries that can involve customer frustration, sensitive financial information and regulatory considerations.
The AI agents were initially trained to handle two specific categories of calls: queries concerning rejected loan applications and requests involving mandate or NOC cancellations.
The scope of the deployment was kept deliberately focused. The AI agent operates only within these predefined call categories. If a customer refers to the Reserve Bank of India during a conversation, the call is immediately transferred to a human specialist without the AI attempting to respond further.
Arrowhead’s technology has also been integrated with Kissht’s dialler and customer relationship management system. This allows relevant customer information and application status to be retrieved before the call is connected. As a result, customers are not required to repeatedly verify basic information or explain the same issue after a transfer.
One of the principal technical challenges during development was reducing the delay between conversational turns.
“When we started, latency was around one second. We built our own small language model and brought that down to around 500 milliseconds, which is among the lowest in the industry,” said Devyani Gupta, Founder of Arrowhead.
Reducing this delay was particularly important for creating a more natural interaction during sensitive customer conversations. Faster response times help reduce interruptions, awkward pauses and the impression that the customer is interacting with a conventional automated system.
According to operational data from Kissht, the AI voice agents are completing calls approximately 30% faster than human specialists handling comparable queries.
“The bot’s average handle time is running about 30% lower than our human agents,” said Shadab, Product and Build Owner at Kissht.
“If the same cost per minute is assumed, that translates into an approximately 30% saving on every call resolved entirely by the AI agent,” Gupta added.
The reduction in average handle time is in addition to the operational benefits created by resolving approximately 88% of calls within the selected categories without human involvement.
Kissht has stated that the efficiency improvement has not resulted in a decline in the customer experience measured during the deployment.
“That is what I would want another CX head to understand,” Shetty said. “We reduced handle time, but the customer experience held steady.”
The deployment has also allowed Kissht to address customer calls received outside the working hours of its support specialists.
Approximately 20% of the company’s inbound support volume is received between 8 PM and 8 AM. Before the introduction of the AI voice agents, many of these calls remained in the queue until the following working day.
“Around 20% of our inbound volume comes between 8 PM and 8 AM. Earlier, that became a queue waiting for the next day,” Shetty said.
Arrowhead’s AI agents now provide round-the-clock coverage for the supported query categories. The same operational policies, escalation rules and guardrails apply to calls received during and outside regular support hours.
Arrowhead and Kissht attributed the speed of the rollout to close collaboration between their respective product, customer experience, and engineering teams.
The implementation process included daily stand-up meetings from the beginning of the engagement. Arrowhead’s team also reviewed live customer conversations to understand how callers described their concerns, where conversations became difficult, and when human intervention was necessary.
Kissht’s implementation team worked directly with Arrowhead’s founders and engineers throughout the deployment. This allowed feedback from customer calls to be incorporated into the system without relying solely on periodic reviews or conventional support-ticket processes.
The two companies used this feedback to refine conversational flows, improve response speed, and strengthen the rules governing transfers to human specialists.
Following the initial deployment, Arrowhead and Kissht are developing an AI agent for EMI and repayment-related queries.
The next phase is expected to cover payment confirmations, auto-debit outcomes, duplicate deductions, late-fee status, foreclosure requests, NOC timelines, and CIBIL-related timelines.
Because these conversations involve transaction-specific information, the new agent is being developed with stricter controls. One of its core instructions is described as “money facts, absolute,” meaning the system must not independently calculate, estimate or round financial information.
The expansion represents a significant progression from handling defined service queries to managing conversations in which an inaccurate response could directly affect a customer’s understanding of a payment or financial obligation.
Kissht said the decision to proceed with the repayment use case followed the operational performance of the first deployment and the ability of the system to maintain customer experience while reducing handling time.
| Metric | Result |
| Share of total inbound volume handled by month two | 40% |
| Calls resolved without human involvement | Approximately 88% |
| Average handle time compared with human specialists | Approximately 30% lower |
| Estimated savings on fully automated calls, assuming the same cost per minute | Approximately 30% |
| Customer experience | Held steady |
| Conversational turn latency | Approximately 500 milliseconds, reduced from around one second |
| Inbound volume received between 8 PM and 8 AM | Approximately 20% |
| Support availability | 24/7 |
| Call direction | 100% inbound |
| Current use cases | Loan rejection queries and mandate or NOC cancellation requests |
| Use case under development | EMI and repayment support |
Kissht is an Indian digital lending platform that provides consumer credit through its Ring app. Its offerings include personal loans, business loans and loans against property, with a focus on serving India’s underserved and emerging middle-class consumers.
Arrowhead develops enterprise-grade conversational AI voice agents for organisations managing customer interactions at scale. Headquartered in Bengaluru and backed by Stellaris Venture Partners, the company primarily works with banking, financial services and insurance organisations across inbound customer support and outbound engagement. Arrowhead develops its own low-latency speech and language technology for multilingual conversations in India.
Media Contact
Garv Jain
Founder’s Office, Arrowhead
Email: garv@arrowhead.team
Phone: +91 96095 21113
Website: arrowhead.ai
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