Analytics & answers you can trust, explain, reuse & improve.
Can you stand behind your AI-generated analysis?
LangGrant captures the reasoning behind AI-generated analytics — the data used, the definitions, the joins, the calculations and the steps — so your teams and your AI can review it, build on it and improve it.
- TrustSee exactly how the answer was produced, before it becomes a decision.
- ExplainDefend the number in the meeting — sources, definitions and every step.
- ReuseApproved reasoning becomes the starting point for the next analysis.
- ImproveA human–AI learning loop instead of a stream of disposable answers.
Works with the agents, MCP tools, RAG and text-to-SQL you already run. No migration, no data movement.
AI produces the analysis in seconds. Standing behind it is the hard part.
AI is being applied with agents, MCP, RAG and text-to-SQL to quickly produce code, analytics and answers to business questions. But when that code and analysis becomes the basis for a forecast, a report or a business decision — can you stand behind it?
Can you trust the analysis?The answer arrives without the work that produced it. Nothing to check before it becomes a number in a board deck.
Can you explain or defend it?“Which sources? Whose definition of net revenue? Why that join?” — asked in the meeting, answered next week, if at all.
Can your organization collaborate with AI to build on analyses?Reasoning that lives in one person’s chat session is not something a team — or a model — can pick up and extend.
Can you reuse analyses instead of starting from scratch?Next month’s version of the same question is a full re-analysis, re-validated and re-paid for in tokens.
Today, the reasoning behind AI-generated answers disappears into
None of it is reviewable, none of it is shared, and none of it is there next time. The analysis survives. The reasoning does not.
Enterprise Reasoning
Our approach for making AI-generated analytics visible, collaborative, explainable and reusable. We capture the reasoning behind an analysis — so that teams and AI can review it, build on it and improve it.
Illustrative. Every field above is a real property of a plan, not a mock-up of one.
Because successful analyses are persisted and reused, prior approved reasoning becomes the starting point for future analysis —
reducing both re-validation and token consumption.
Two ways to start.
Add Enterprise Reasoning to the AI data stack you already have, or pilot the LangGrant product on your own data and business questions.
Add Enterprise Reasoning to your existing AI data stack
We work with your existing agents, MCP tools, RAG, text-to-SQL or AI data engineering environment. We add the capabilities to:
- ✓Capture and visualize the reasoning behind analyses
- ✓Review and explain results
- ✓Persist and reuse successful analyses
- ✓Enable collaboration between teams and AI
- ✓Create a foundation for continuous improvement
DeliverableEnterprise Reasoning capability integrated into your existing environment.
Pilot the LangGrant product
Run LangGrant on your data and your business questions. LangGrant provides:
- ✓AI-generated analytics across multiple databases
- ✓Structured reasoning for every analysis
- ✓Drill-down visibility into how results were produced
- ✓Persistent, reusable analyses
- ✓Human–AI collaboration
- ✓Governed, repeatable execution
DeliverableA working pilot using your data and business questions.
Make decisions with confidence — because you can see the reasoning.
AI generates the analysis. Your teams can see it, explain it, build on it, reuse it and improve it.
See and understand it
The sources, definitions, joins, calculations and steps behind every number are visible — in terms a business reader recognizes, without reading SQL.
Trust it enough to decide
Analyses are reviewed and approved before they count. When someone asks “how did we get that?”, the answer is on the screen, not in someone’s memory.
Compound it over time
Every approved analysis becomes an input to the next one, so effort compounds instead of repeating — and re-validation and token spend both fall.
AI becomes a source of continuously improving organizational intelligence,
rather than a source of disappearing answers.
A leader in Enterprise Reasoning for decision intelligence.
LangGrant is the founding author of the new open standard for representing reasoning in a structured format, and comes from the team behind Windocks — recognized by Gartner for database modernization.
Founding author of the Enterprise Reasoning standard
We authored the new open standard for representing reasoning in a structured format, so reasoning is portable across tools and vendors rather than locked inside one product. See enterprisereasoning.org.
Analyst recognition
Recognized leader in database modernization
The team behind LangGrant built Windocks, named in Gartner research for database CI/CD and for machine learning, data and analytics.
Trusted by global enterprises
Shipped into regulated industries — healthcare, insurance, global retail and financial services — where the reasoning behind a number has to hold up to review.
Bring one real business question.
We’ll answer it from your data — and show you the reasoning behind the answer, saved, reviewable and reusable.
- ✓Get the answer — and the why — from the databases you already run.
- ✓See one analysis span multiple databases, using only the tables it needs.
- ✓Watch the follow-up come back from the reasoning you just approved.
Answers expire. Reasoning compounds.