How it works

Every answer starts with context.

Before a query ever runs, Agami assembles the context: what the question means, who's allowed to ask it, and where the answer lives and how best to get it. Agami's agents create it, apply it on every question, monitor it in production, and update it over time. Your team reviews and approves.

Created

Agami drafts your context from your databases, existing models, docs, and wikis. Your team approves.

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Applied

Agami answers each question from your approved context and flags anything it cannot ground in it.

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Monitored

Agami scores every answer in production and surfaces drift to your data team.

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Updated

Agami turns scores and feedback into tested refinements your team approves.

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Modeler agent

How your context is created.

Agami reads your databases, any existing models, and the docs and wikis where your business knowledge lives, then drafts the definitions, metrics, and entities. Your team reviews and approves. Nothing ships unsigned.

Step 1

Introspect

Reads your databases, plus any existing models, docs, and wikis.

Step 2

Draft

Writes definitions, metrics, and entities into the semantic layer.

Step 3

Approve

Your team reviews and publishes. Nothing ships unsigned.

Analyst agent

How your context is applied.

Agami maps each plain-language question onto your context, then returns the SQL, a chart, and a short insight. It checks its own answer against your approved definitions and marks it governed or flagged.

  1. You ask

    “How is gross margin trending vs plan?”

    VP, Finance · Asked in Claude

  2. Access

    finance
    marketing · sales · HR · CRM
    Authorized

  3. Semantics

    Definition gross-margin
    Memory 14 similar queries
    Validators 4 of 4 passed
    Grounded · 96%

  4. Routing

    Plan partition pruned · 1.2M rows
    Policies row + column applied
    Freshness loaded 2h ago
    Source cached · cost-bounded
    Executed

  5. You get

    Gross margin · Q2

    62.4%

    ↑ +1.8 pts vs plan

    Core 68%
    Pro 61%
    Ent 58%

    Mix shift to Pro is lifting margin.

    Governed

Every answer is marked Governed when it is built from definitions your team approved, or Flagged when it improvises an undeclared join or a hand-rolled metric, so no one mistakes it for an official number.

Operator agent

How your context is monitored.

Agami deploys in your cloud, ships every change through your CI, then scores each answer in production against your context: SQL correctness, relevance, entity accuracy, and output quality. Anything below your threshold is surfaced to your team for review.

Shipped v14 through your CI

Answer graded

Q2 ARR pacing · +14% above plan

0.94

Governed
SQL correctness 0.94
Relevance 0.90
Entity accuracy 0.96
Output quality 0.85
“Churn by segment” scored 0.58 · flagged to your data team 1,240 graded today · 92% above threshold
Optimizer agent

How your context is updated.

Agami turns production scores and user feedback into proposed refinements. Each one is impact-tested against your golden datasets, then your team approves what ships.

Step 1

Signals in

Production scores, user feedback, and failed queries feed the loop.

Step 2

Proposes a fix

Agami drafts a refined definition or example.

Step 3

Impact-tested

Each change passes your golden datasets before review.

Step 4

You approve

Your team approves what ships, and the pass rate climbs.

Agami's agents run the whole lifecycle. Your team approves what ships, or hand approvals to Agami and run it fully managed.

See it on your data.

Try the demo, or book a 30-minute conversation with the founders.

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