OLIVEAtlas
Olive Atlas

The system of record for enterprise AI work.

Atlas shows what each AI process costs and the value it delivers, then helps you test, improve and protect it.

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Read-only to start · Never sees prompts, responses or customer data · No change to your AI traffic

Work mapIllustrative
  • Issue-to-resolution
    Fund
    AI cost$12.4K
    Value$48KMeasured
  • Idea-to-release
    Test
    AI cost$9.8K
    Value$21KEstimated
  • Order-to-cash
    Fix
    AI cost$6.1K
    Value$7KEstimated
  • Quote-to-contract
    Measure first
    AI cost$3.2K
    Value—Unknown

Your AI bill is visible. What it buys isn’t.

Providers show tokens and spend. Gateways show calls. Nobody shows which AI step helped resolve a ticket, ship code or stop fraud, so AI gets funded on faith and cut on guesswork.

Olive Atlas

How Atlas works

  1. Connect.

    Add a small adapter to your AI apps and agents. After each step it sends Atlas a short note (workflow, step, model, cost and time) with content stripped first.

  2. Map.

    Atlas places each AI step in your own processes, next to the people and systems around it. Owners confirm what Atlas observed and why each process exists.

  3. Measure.

    Atlas links each step to the result it served and builds an AI profit-and-loss for every process, including the people time AI creates for review.

  4. Test.

    Atlas tries cheaper models and better ways of working on a small, random slice of live work, with safety limits and automatic rollback.

  5. Recommend.

    Atlas ranks where the next AI dollar should go (fund, fix, cut, protect or measure first) and labels the evidence behind every call.

  6. Protect.

    When a model, vendor or rule changes, Atlas shows which processes are affected, which have a tested backup and what to protect first.

Olive Atlas

What you see in Atlas

  • Work map.

    Every process, why it exists, what its AI costs and what it’s worth.

  • AI profit-and-loss.

    Cost and value for every process, with each number labeled measured, estimated or unknown.

  • Executive view.

    Where AI money goes, what it creates and where margin leaks.

  • Tests.

    Each proposed change with its safety limits, results and savings, counted only after a full week closes.

  • Continuity.

    For each process, what happens if a model or provider fails, and the tested backup.

  • The record.

    Every test, approval and change, versioned and exportable. You own it.

An animated executive console moving from economics to controlled action in four connected states, following one workflow throughout: Support classification. All figures shown are illustrative and no external action is performed.

Executive console

Observe → Recommend → Control

Illustrative analysis

Cost per successful outcome increased 18%.

WorkflowSupport classificationTraced to one business workflow

Total AI spend

$84,260

Month to date

Forecast

$101,400

Full month, current routing

Cost per successful outcome

$2.14

Up +18% on last month

Spend by business workflow

  • Support classificationCost driver$26,180
  • Document review$18,940
  • Sales research$14,320
  • Code assistance$13,110

The rise traces to one workflow: Support classification.

AI spend$84,260
Savings identifiedAnalysing
Quality statusNot yet assessed

From AI consumption to business performance.

State 1 of 4 · economics
Security

Built so your security team can say yes.

  • Nothing sensitive leaves your environment.

    Prompts, responses, attachments, customer data, credentials and employee identities stay with you.

  • Beside the request path, not in it.

    Atlas adds no delay, and if Atlas is unavailable your AI keeps running.

  • Changes go through your own systems.

    Owners approve, IT applies changes through your gateway, and every change can be undone.

The request path

Your AI apps
Your gateway
Models

Beside it, after the fact

Atlas adapter
Olive Atlas

A short note after each step, with content stripped first. Nothing here sits in the request path.

Atlas shows what to change. Model Fabric makes the change.

Apply approved changes through your own AI gateway, or turn on Model Fabric to route and govern requests directly when you’re ready.

Explore Model Fabric

Built on an engine already in production.

Atlas runs on the same engine behind Olive’s decision intelligence work at a global game publisher.

FAQ

Does Atlas see our data?

No. Atlas receives a short record of each AI step after it finishes. Prompts, responses and customer data are removed before anything leaves your environment.

Does Atlas sit in the request path?

No. It reads a copy after the fact, so it adds no delay and your AI keeps running if Atlas is down.

What do we need to connect?

A small adapter in your AI apps or agents, plus read access to the system where results live, such as ServiceNow, Jira or GitHub.

How is value measured?

Atlas links each AI step to a business result through a shared ID, such as a ticket number. Labor value is always shown as an estimate, never as cash.

Do we have to change models or vendors?

No. Atlas works with the AI apps, gateways and models you already use.

Start with one process.

Most teams start with one workflow, such as support or code review.

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