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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Uvi, the enterprise software company operated by Naboo Research Ltd., announced a $7.5 million seed round on October 14, 2026. Its context-reasoning layer is designed to let AI agents understand a company’s processes and history without repeatedly searching the same systems; Uvi says that approach can reduce answer costs by as much as eightfold in its own benchmarks.
What happened in Uvi’s funding round
CT Innovations led the seed financing, with Cardumen, Mana VC and 91 Ventures participating. Uvi says it will use the capital to build a US team, expand sales and continue product development. The company is positioning the product as infrastructure for enterprise agents rather than as a standalone chatbot or model.
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Uvi is the operating name associated with Naboo Research Ltd. The announcement came on October 14, 2026, as companies are moving from experimental assistants toward agents that must execute work across multiple internal systems.
What does Uvi do for AI agents?
A newly deployed enterprise agent may know how to call tools or generate text but still lack the company-specific knowledge needed to act reliably. Relevant information is usually distributed across Slack, Jira, Confluence, Salesforce, code repositories, meeting notes and other services. An agent can spend a large share of every request rediscovering terminology, prior decisions, dependencies and standard procedures.
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Uvi co-founder and chief executive Gilad Salinger described the cause as “structural, not about intelligence.” The company’s thesis is that agents become expensive and error-prone when each one has to reconstruct the same business context from raw records.
A context-reasoning layer beneath agents
Uvi combines a knowledge graph, entity mapping and a custom semantic layer. The graph connects related records such as support tickets, pull requests, feature flags, discussion threads and documents. Entity mapping helps identify that different systems are referring to the same project, service, customer or incident. The semantic layer is intended to resolve company-specific vocabulary that a general model would not reliably understand.
Reconstructing decisions over time
The system also aims to recover the reasoning behind changes. For example, a decision made in a chat thread may later be reversed in a document comment. Linking those events gives an agent a timeline instead of a disconnected list of search results, helping it distinguish the current instruction from an obsolete one.
Uvi’s reported cost and speed results
The figures below come from Uvi’s 2026 benchmark reporting. They compare an agent using Uvi’s context layer with a do-it-yourself agent searching the same enterprise sources, using the same model or an equivalent setup. They are company-reported results, not an independently audited industry average.
| Measure | Agent without Uvi | Agent with Uvi | Reported result |
|---|---|---|---|
| Cost per answer | $0.75–$1.41 | $0.10–$0.16 | Lower per-answer cost in Uvi’s benchmark |
| Open-ended questions that trigger search loops | Baseline not stated separately | Uvi context layer | Up to 46 times cheaper and twice as fast, according to Uvi |
The practical explanation is reduced repeated retrieval: instead of making an agent rediscover the same relationships on every request, the context layer supplies a structured representation that can be reused by multiple agents. Actual savings will depend on data volume, source quality, model pricing, permissions and how often requests require broad investigation.
Model portability and integrations
Uvi says its business context sits outside any single model or interface. Companies can use it with Claude, Gemini, GPT, Claude Code, Cursor and other agent environments. That separation is intended to let an organization change models or deploy several agents while preserving the same mapped entities, terminology and historical relationships.
The approach also changes what an integration must do. Rather than giving every agent a separate collection of connectors and search prompts, an organization can expose a common context layer that draws from its existing systems. The breadth and freshness of those connections remain important implementation factors; Uvi’s public description does not establish a universal list of supported connectors or update intervals.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsSecurity and permission enforcement
Uvi says it can run inside a customer environment or virtual private cloud. Its agent-aware permissions are enforced during graph retrieval, so an agent should return only information that the person making the request is already authorized to see. Enforcing access at retrieval is meant to avoid adding a separate security retrofit after building a knowledge graph.
That model does not remove the need for ordinary identity, source-system and audit controls. Customers still have to configure permissions correctly in connected systems and decide how long indexed context should be retained.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Customers and a concrete workflow example
Independent reporting identifies monday.com, Lemonade and Melio as customers. Uvi’s own site also features testimonials from Melio and Global-e.
Linking engineering records
In the monday.com example, Jira tickets, pull requests and feature flags are linked so an agent can follow the relationships among a request, the code change that addressed it and the rollout control that governs its release. That is different from returning three unrelated search results: the agent can use the connected history to explain what changed, why it changed and whether the change is active.
Why investors see a large infrastructure gap
Gwen Cheni of CT Innovations said, “Most are still very far away,” referring to companies’ attempts to build context at scale. The comment reflects a distinction between demonstrating an agent in a controlled workflow and maintaining a dependable context system across many teams, tools and changing decisions.
Uvi’s pitch is therefore broader than faster retrieval. It is selling persistent business context that can be shared across agents, model providers and interfaces while retaining company-specific meaning and access rules.
Quick Recap
What the announcement does—and does not—prove
- The financing confirms investor backing for Uvi’s product direction, but no valuation or revenue figure has been disclosed in the available announcement.
- The cost and speed numbers describe Uvi’s own benchmark design; no independent audit or market-wide comparison has been established.
- Lower token or retrieval spend does not automatically mean better answers. Accuracy still depends on source completeness, entity matching, current permissions and the quality of the underlying records.
- Uvi is an enterprise software platform, not a physical product, and the announcement does not establish a consumer offering or a verified referral program.
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