The insight that changes the decision
The Insight Analyst reads your data for the finding that changes a decision, controls for the confounds that fool a naive read, and says plainly when a difference is only noise.
Segment performance · Q2
Insight AnalystComparing segment performance for the quarter. Looking for the decision-changing insight.
Reading conversion by segment4sSegment C has the highest raw conversion. Before I call it, I want to know why.
Breaking conversion down by deal size and source6sC wins on volume of small deals. On revenue per segment, B is well ahead.
Posting the insight and the recommendation1s
How it works
Dataset refreshedA/B test finished“which segment wins?”Weekly metrics · Mon
Insight posted · lean into BConfound controlled forNoise called as noiseAnalysis written upTriggered by your data
A refreshed dataset, a finished test, or a question in Slack starts the analysis. The agent reads the numbers itself.
Finds the driver, not the headline
It controls for the confounds a naive read misses, reports the finding that would change a decision, and refuses to name a winner when the difference is only noise.
Reports the insight where you work
The finding lands in Slack or a doc: the recommendation, the reasoning, and the honest caveat when the data cannot yet support a call.
Without Relevance
With Relevance
A dashboard shows the numbers and leaves the reader to guess what they mean.
The agent reads the data and reports the one finding that would actually change a decision, reasoning stated.
The top-line leader wins the meeting, confound or not.
The agent controls for the obvious confounds and reports the real driver, even when it reverses the naive ranking.
A one-point gap gets a winner crowned and a plan built on it.
The agent checks whether a difference is real before naming a winner, and says when it is within noise.
Only the metrics someone thought to chart get looked at.
Every segment and cut in the data gets the same scrutiny, not just the ones on the dashboard.
Two analysts read the same numbers and reach two different calls.
One analytical method applied to every dataset, so the call does not depend on who ran it.
A confident recommendation gets made even when the data cannot support one.
When the difference is not significant, the agent says so rather than inventing a winner.
Held to a quality bar, on every run
Every analysis is checked against eval test cases written for this exact job before it reaches the team. If a run fails the bar, it never ships.
Insight AnalystSampling 2% of live runs · 94% passing this week
Shaped by your team, not a template
Experts and engineers tune Insight Analyst to your playbooks. Every change ships through the same evals.
Drag and drop
Compose agents and workforces on a visual canvas. Drag in agents, tools, and approvals in a flow anyone on the team can read.
Drag and drop
Compose agents and workforces on a visual canvas. Drag in agents, tools, and approvals in a flow anyone on the team can read.
Ticket TriagerBuild with AI
Describe the agent in plain language and Invent builds it: the prompt, the tools, and the evals to prove it works.
Build with AI
Describe the agent in plain language and Invent builds it: the prompt, the tools, and the evals to prove it works.
Claude Code
CodexBuild with MCP
Engineers drive the same platform from Claude Code, Codex, or Cursor. Create agents, link knowledge, and run evals over MCP.
Build with MCP
Engineers drive the same platform from Claude Code, Codex, or Cursor. Create agents, link knowledge, and run evals over MCP.
Built for enterprise teams
Run agents on your real data with the access controls, audit trails, and residency guarantees enterprises require all built in.
Security & data privacy
- Data residency
- PII masking
- Audit logs
- No training on your data
Access & controls
- Role-based access control
- SSO / SAML
- Human-in-the-loop approvals
- Version control
Monitoring & oversight
- Real-time monitoring
- Full agent tracing
- Cost visibility
- OTEL & Delta Share export
"The ability to be vendor agnostic and the ability to scale across a breadth of functions is a really key feature."
Levi Watters
Partner, KPMG Australia
"The key for us was how we can modularize industry knowledge and the best playbooks, and apply it."
Allen Roh
Senior Marketing Manager, Autodesk
"We're looking for every place where AI can allow sellers and customer success reps to be more engaged with customers."
Rob Giglio
Chief Customer Officer, Canva
"The ability to be vendor agnostic and the ability to scale across a breadth of functions is a really key feature."
Levi Watters
Partner, KPMG Australia
Team it up with more research agents
Market briefMarket Researcher
Researches a market from live sources into a sourced brief.
Source Synthesizer
Reduces many sources to cited findings, contradictions and all.
Themes written upInterview Synthesizer
Turns customer interviews into themes with verbatim evidence.
Every agent you add shares one stack
These agents all run on one platform: one gateway, one router, one eval suite, one audit trail. Every agent after the first ships faster.
- Triggered by key events or signalslike Zapier
- Given access to contextlike Zep
- Connected to your appslike Composio
- Access to all LLMslike OpenRouter
- Performance evaluatedlike Braintrust
- No-code agent builderlike Dust.tt
- Coordinated into teamslike CrewAI
- Kept alive through long-running worklike Temporal
- Traced at every step of every runlike Langfuse
Put the Insight Analyst to work this quarter
We partner with enterprise teams to take this work off their plate. An agent built with you, proven against your quality bar, and live in weeks.