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Overview AI Usage Map & Score Action Engine Outcomes Methodology

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Turn your AI usage into
a ranked action plan.

The Action Engine finds the signals in how your teams use AI and ranks what to do next, from coaching a team to actioning an in-flight deal.

Coaching

Teach teams what your best AI users do

Teach a group: the renewals team3 of 11 reps · 82% vs 64% renewals won

Deals

Spot next steps on live accounts

Run the prep agent on three open dealsNo prep in 14 days · 38 vs 47 days to close

Agents

Fix agents that fail, stall, or overspend

Renewal-risk agent dropped the buyer9 of 40 runs failed this week, up from 2

Governance

Catch and resolve policy risks

Card numbers pasted into prompts6 prompts in 3 teams this month

Spend

Attribute spend by model, topic, and skill

Move four skills to a smaller modelSame pass rate · 38% fewer tokens

Automation

Build, spread, and repair skills

19 of 31 renewal briefs written by hand19 by hand vs 12 with the skill

How the plan gets built

It starts from your AI Usage Map and AI-Use Score. No one ranks it by hand.

  1. Map the work. Every conversation from your AI tools is classified by topic, output and complexity, then rolled up by team.
  2. Score each team. Five dimensions turn that map into one AI-Use Score per team, tracked over time.
  3. Fire the signals. About 70 detectors scan the map: rework on the same task, work done by hand that a skill covers, an agent that stalls, sensitive data in a prompt.
  4. Rank the actions. Signals about the same team, topic or skill become one action, ranked by the score points it should move. Policy risks go first.

Self-Learning Skills turn repeat work into shared skills Beta

Automation actions start the skills work: they merge duplicate skills, keep one skill per job, and keep every tool on one inventory.

Try it: move a skill through the pipeline.

1
DetectWe spot work your team repeats.
2
TestEach candidate runs on your past work.
3
PublishWhat passes reaches the whole team.
4
ImproveReal use sharpens each skill over time.
DetectBring skills you've already built.They run the same pipeline. 0
TestYou approve every skill.Each is scored against what your team did. 0
PublishSkills reach your team's tools over MCP.Their use feeds your score. 0
ImproveYou set the pace of change.Evals run on real use, and fixes fold back in. 0

Drag a card to the next column, or click it to see what happens next.

Three steps from AI usage to business outcomes.

Each step has its own part of SightLift.

Read the methodology →

Get your action plan from your own AI usage.

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