SightLift takes your team from ad hoc, unmeasured AI use to deliberate, data-driven AI use, built from real usage and the systems you already run.
Works with Claude, ChatGPT, Gemini, Copilot, and more
You rolled out the seats. What you still can't show is meaningful usage patterns, skill usage, or what the business got back.
Our visibility into how the team uses AI is a D+ at best.
Nine people, solving the same problem differently.
Skill shares and lunch-and-learns just don't stick.
Seats bought, usage up. That's the whole dashboard.
Some people are great. Some are never opening Claude.
It boggles my mind there's no skill usage data.
Most teams we meet sit between guesswork and governance. You can't lift what you can't see.
SightLift turns the AI usage data you already have into a score and enablement plan you can stand behind, skills that learn with every use, and proof for the board.
What your team actually does with AI, day to day, drawn from the usage data your AI tools already keep.
A single metric for AI usage, built from the factors you care about, with the ranked moves that lift it.
Skill libraries go stale on the shelf. Ours are detected in your real usage and learn with every use.
"Seats bought and usage up" isn't an ROI story. See what your AI spend is buying, across every tool.
We do the work with you: practitioners alongside your team, with your tools, for your goals.
One tool's output is the next tool's input: the map feeds the score, the score picks the skills, the skills show up in ROI.
Book a demoThree steps stand between the data you already have and lift you can measure. Everything ships into the tools your team already uses.
We wire in every AI surface with your IT team, plus the business systems you already run.
We enrich that AI usage data into the map and the score: topics, teams, cost, and skill use.
Ranked actions and shared skills flow back into the tools your team already works in.
See pricing and the 90-day pilot →
Built for the operator scaling the business: you carry a target, and you don't need an AI center of excellence to hit it. We'll walk you through SightLift on your own data.
Engagement details live on the pricing page.
Prefer email? Reach us directly at sales@sightlift.ai.
Patterns over people
AI conversations can feel personal, even on company accounts. We respect that, so SightLift starts shallow and opens up only as you choose.
Never trained on, never sold
SightLift trains no models on your data, and your data is never sold. Where it informs cross-company benchmarks, it is anonymized and aggregated first.
SightLift is a platform and service that scores your team's AI usage into a single AI-Use Score and recommends the ranked moves that lift it. Behind the score sits Self-Learning Skills, every team's skills in one place: discovered in real AI work and improved continually, plus a team of expert partners alongside yours from setup through every action.
SightLift is built for the operators scaling the business: chiefs of staff, operating leaders, RevOps, and heads of department who carry a target. We do the ingest, scoring, and building, so you get smart recommendations with a team behind them.
All major models and surfaces. SightLift works with Claude, ChatGPT, Gemini, Copilot, and more, across chat, code, and agents. It can also join AI usage to business outcomes from systems like HubSpot or Salesforce and from call transcripts. You start from AI work you already have, with no new tooling for your team.
We connect to the AI tools your team already uses (Claude, ChatGPT, Gemini, Copilot, Bedrock, and more), working with your IT team during setup. Your team keeps working exactly as they do today: no new tooling, no plugins to install, no behavior change. Business systems like your CRM or data lakes can join as an optional add-on.
The AI-Use Score is a single, weighted metric for your team's AI usage, built from the factors you care about most, like adoption, sophistication, efficiency, reuse, and governance. Weight it to your strategy, break it down by team, geo, or department, track it over time, and audit every change back to its cause. See it explained at sightlift.ai/score.
SightLift discovers skill candidates in your team's real usage data, like six people writing the same renewal prompt, and turns proven patterns into shared skills. Every candidate for improvement is human-vetted before it ships, delivered to your team via MCP, and evaluated continually so it sharpens as usage grows. To your team, it just feels like their AI got better.
SightLift is an annual subscription: the platform and our expert team, scoped to your team. You start with a 90-day pilot, starting at $12,500 with implementation included: platform access for the working group you choose, a clear read on how your team actually uses AI, and our team's findings. From there you continue into the annual subscription. The expert service is part of the product, not a consulting engagement. Business integrations (data lakes, CRM, call transcripts) are an optional, custom add-on. Details at sightlift.ai/pricing.
No. SightLift's default lens is patterns in the work: topics, trends, and teams, scored and automated at that level. Individual views exist and are yours to configure, and sensitive detail sits behind a separate clearance.
No. SightLift lives in your existing tools, so your data is never exfiltrated or used to train foundation models, and its AI subprocessors process it under commercial terms that exclude training. Your data is encrypted with AES-256 at rest, isolated per tenant with row-level security, and the governance program is built for SOC 2 Type II and ISO 27001, 27701 and 42001 alignment. The controls and the documents for a security review are on our security page.
No. You don't need an AI center of excellence or any AI resources of your own. We do the ingest, scoring, and building, and our team applies judgment across plan vetting, skill review, and leadership readouts, so there's a human in the loop on every action. You start from AI work your people already generate, with no new tooling and no behavior change.
You start from AI work you already have, so there's nothing to roll out. Expect your first data playback about two weeks after connecting, and your first full readout, with your score and ranked enablement plan, inside 30 days. Outcome views deepen from there as usage accumulates.
Some teams start there: one engineer hand-pulling usage exports, a skills wiki, a dashboard someone maintains on the side. It works until that person is busy. Homegrown stacks age fast and carry a bus factor, and per-skill visibility is hard to keep even for dedicated central AI teams. SightLift is the maintained version of that stack, with ingest, scoring, skill lifecycle, and evals kept current for you. If you're weighing build vs. buy, the assessment leaves you with the data to make that call either way.
No. SightLift is headless where it counts. Skills ship over MCP into the tools your team already uses, reporting arrives as readouts and a dashboard for the people who need it, and your team keeps working exactly where they work today. Most people just notice their AI getting better.