AI workflow intelligence

Know which AI work is worth repeating.

Tokenly connects AI usage and token spend to the work your company ships—without monitoring people. See which workflows create value, standardize high-confidence patterns, and assess what may be ready to automate.

Open the synthetic workspace

Synthetic demo5-person privacy floorNo prompt content

Tracked usage90.2Mtokens

Linked68%to outcomes

Outcome rate1.21×vs. workflow baseline

WorkflowVs. workflow baseline

Support response draftingCustomer ops

1.42×

PR review preparationEngineering

1.29×

Account researchRevenue

1.11×

Associational evidenceCoverage 68% · n=42 linked outcomes30-day synthetic window

Connection roadmapExamples, not live integrations

AnthropicGitHubLinearZendesk

BUILD STATUS / HONEST BY DEFAULT

What works today.

The browser demo is real. The company data is not. Tokenly is an instrumented product concept built to test one decision: can AI usage be linked to a verified workflow outcome without monitoring people?

Available nowInteractive synthetic workspaceMetrics, workflows, privacy controls, and automation review.

First pilotGoverned CSV importUsage exports joined to one buyer-defined outcome.

Not claimedNo live connectors yetNo customer logos, ROI claims, or hidden employee scoring.

01 / THE GAP

The bill tells you where tokens went. Not what changed.

Usage dashboards stop at spend and adoption. Tokenly builds the missing link between an AI session and a business outcome, without pretending correlation is causation.

Illustrative synthetic example · associational link

AI usage record

Claude Sonnet 4.5Customer operations

Tokens: 18,420
Cost: $0.31
Workflow tag: response-draft

Tokenlyconfidence 0.86

Outcome record

Ticket #8421 resolvedZendesk / billing queue

Resolution time: 8m 14s
Reopened: No
QA score: 96 / 100

02 / THE METHOD

Measure the workflow, not the person.

Tokenly treats token efficiency as a diagnostic. Managers see patterns they can improve, not a leaderboard that rewards cheap prompts or punishes hard work.

Start with governed exports

A first pilot would use CSV exports to validate model, token, cost, team, and time fields before adding connectors.

Link work to outcomes

It would match tagged sessions with delivery, CRM, support, and operational records.

Normalize the comparison

Comparisons stay within like workflows across time, quality thresholds, and business context.

Promote what works

High-confidence patterns can become playbooks, then candidates for governed automation review.

03 / THE PRODUCT

One learning loop from spend to automation.

Start with visibility. Earn the right to recommend a workflow. Automate only after the evidence, controls, and owner are clear.

Synthetic interface examples

Workflow map

See where AI appears in a process and which outcome follows.

Privacy by default

No prompt content required. Team-level reporting, minimum cohort sizes, and visible metric definitions keep analysis useful.

Metadata-first collection
Configurable retention
Employee-visible methodology

Automation queue

Rank candidates by evidence, repeatability, readiness, and risk.

Support response drafting85Ready to review

Internal policy Q&A75Needs owner

04 / TRUST MODEL

Useful without reading the work.

The first version uses provider metadata and outcome events. Prompt or response content stays out of scope unless a customer deliberately enables a governed use case later.

Aggregate firstDefault to team and workflow views.

Show the denominatorEvery score explains its inputs and coverage.

Keep a human ownerRecommendations do not deploy agents on their own.

DESIGN PARTNER PROGRAM

Bring one workflow. We'll help you find the signal.

We're preparing the first measurement pilots around one workflow and one buyer-defined outcome. The pilot starts with governed CSV exports, not a platform migration.