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Grounded Answers
Answers drawn from your content, with the sources shown so they can be verified.
- Source-cited responses
- Answers assembled across documents
- Clear signals when evidence is thin
Enterprise Knowledge
Enterprise Knowledge.
Answers grounded in what you already know.
Search and answers across your organisation's own information — cited, permission-aware and measured for quality in production, rather than a demo that impresses once and quietly stops being used.
The problem
Knowledge products fail in a specific way.
The model works, the demo lands, and adoption never arrives — because the system was tuned on a curated set of documents rather than the real corpus, the interface hides how confident it actually is, and there is no way to distinguish a good answer from a merely plausible one at scale. These are product problems, not model problems.
Intellivetrix treats them as such. Quality baselines are agreed before launch rather than after. Answers show where they came from, so a reader can check them. And what gets measured in production is whether an answer was useful, not whether the request returned successfully.
The result is a capability people keep using: it covers the content they actually need, it respects who is allowed to see what, and it stays accurate as the underlying information changes.
Capabilities
What Enterprise Knowledge provides.
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Permission-Aware Access
People see only what they were already entitled to see, checked at the moment of asking.
- Existing permissions respected
- Per-user and per-tenant scoping
- No shadow copy of access rules
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Broad Content Coverage
Documents, databases, wikis and records systems brought into one place people can ask.
- Works with existing content sources
- Kept current as sources change
- No migration of your data required
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Applications & Integration
Available in the tools people already use, as well as through its own interface.
- Embeddable in existing applications
- Programmatic access for your own products
- Enterprise authentication
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Interfaces That Earn Trust
Provenance, uncertainty and easy correction do more for adoption than marginal accuracy gains.
- Citation and source display
- Confidence and fallback states
- Feedback capture
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Quality in Operation
Whether answers are still good after launch is a number, not an assumption.
- Agreed quality baselines
- Continuous quality monitoring
- Feedback-driven improvement
How adoption works
From first content source to a capability people rely on.
Quality measurement runs through every stage rather than appearing as a gate at the end.
Assess
Priority QuestionsContent AuditAccess RulesQuality Baseline
Configure
Content SourcesPermission MappingGuardrailsDeployment Model
Prove
Baseline EvaluationUser TestingCost & Latency Check
Operate
Quality MonitoringFeedback LoopsContent FreshnessSupport
What matters
What distinguishes a product from a pilot.
Measurement from day one
Quality targets are defined before launch, so “is it good enough” becomes a measurement rather than an argument.
Fitted to your knowledge
The capability is configured around your actual content, its update cadence and its access rules — not a generic default that works on a demo corpus.
Trust before accuracy
Provenance, uncertainty and easy correction do more for adoption than an incremental gain in model accuracy.
Operable by your team
Documentation, dashboards and runbooks ship with the platform, so your team can run and extend it without depending on us.
Common questions
Frequently asked.
What does Enterprise Knowledge do?
It makes your organisation's own information usable by AI. People ask a question in their own words and get an answer grounded in your content, with the sources shown, so the answer can be checked rather than taken on trust.
How is this different from the search we already have?
Conventional search returns documents and leaves the reader to assemble the answer. Enterprise Knowledge answers the question directly, drawing on several sources where needed, and cites where each part came from. It also handles questions phrased the way people actually ask them rather than as keywords.
How do you stop it inventing answers?
By grounding every answer in retrieved content and showing the sources, by measuring answer quality against agreed baselines rather than assuming it, and by designing the interface to communicate uncertainty instead of always sounding confident. Where the platform cannot support an answer, it says so.
Will it expose information people should not see?
No. Access follows the permissions already defined in your source systems. A user only ever receives answers drawn from content they were already entitled to read, and that check happens at answer time rather than being baked in when content was first indexed.
What kinds of content can it work with?
Documents, databases, wikis, ticketing systems, records systems and other enterprise sources. The platform works with the data platforms and permission models already in place rather than proposing to replace them.
How is quality measured after launch?
Quality baselines are agreed before release and monitored continuously afterwards, alongside user feedback. That is what tells you whether answers are still good six months in, when the content has changed and nobody is watching the launch dashboard any more.
Can it run in our own environment?
Yes. Enterprise Knowledge is a capability of the Enterprise AI Platform, so it deploys self-hosted in your own cloud, as managed SaaS, or hybrid where content has to stay in a particular jurisdiction.
Related products
Knowledge sits on a platform.
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Enterprise AI Platform
A reusable platform for developing and operating enterprise AI solutions.
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Intelligent Automation
Orchestration of AI-driven workflows that carry real work to completion, safely.
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Platform Foundations
The cloud, delivery and security foundation the platform and your own workloads share.
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AI Cost Optimization
Improve AI efficiency and keep enterprise AI spend predictable as adoption grows.
Next step
Make your own knowledge answerable.
Talk to us about Enterprise Knowledge — which content, which questions, and what has to be true about permissions and quality before it goes live.