Take your team from ad hoc, unmeasured AI use to deliberate, data-driven AI use.
Works with Claude, ChatGPT, Gemini, Copilot, and more
You own the outcome. IT owns the console. Leadership wants a readout, and you have no data of your own yet.
Carrying the CEO's AI push on top of everything else. You need a starting point and actions ready to run, with a team that does the work with you.
AI adoption became a people problem, so it became yours. You need a definition of good AI use for each team, and a readout you can take upward.
You carry a target and sign for the seats. You need to know what they're buying, which teams are pulling ahead, and which ones to lift first.
Some people are great. Some are never opening Claude.
Everybody's a builder now. I'm not sure we're any faster.
Seats bought, usage up. That's the whole dashboard.
Skill shares and lunch-and-learns just don't stick.
Nine people, solving the same problem differently.
Our visibility into how the team uses AI is a D+ at best.
Most businesses still can't measure what AI changes. You can't lift what you can't see.
SightLift turns the usage data you already have into a score and an Enablement Plan you can stand behind, skills that learn with every use, and a readout you can take to leadership.
One picture of what your team actually does with AI, across every tool, drawn from the usage data those tools already keep. Patterns over people: by topic and team, not by individual.
One number for your team's AI use, weighted to your strategy and tracked over time, with the moves that lift it ranked by impact.
Skill libraries go stale on the shelf. Ours are found in your team's real usage, kept current in one place, and sharpened with every use.
"Seats bought and usage up" isn't an ROI story. Join AI usage to your CRM and systems of record, so each AI effort shows what it changed and what it cost.
We do the work with you: practitioners alongside your team, with your tools, for your goals.
What you're building toward: more consistent AI use across your teams, one number you can track quarter to quarter, and skills that get better the more they're used.
Book a demoThis is the SightLift methodology: map the usage, join it to business outcomes, lift what works, and run it again as the business and AI change. We run each step with you.
IT keeps the tools. We wire in every AI surface alongside them and shape the usage into one record: topics, teams, skills, and the power users nobody had on a list.
We join that usage to the systems you already run, like your CRM, so each AI effort shows what it changed and what it cost.
Ranked actions and shared skills flow back into the tools your team already works in. What your best people figured out raises the floor for everyone.
Built for the leader who owns AI adoption: you carry the 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.
The leader who was handed AI adoption and owes leadership a result. Usually that is a chief of staff, a COO, or a chief people officer. Sometimes it is a CRO or the head of RevOps whose remit grew to include AI. You own the outcome, IT owns the tools, and you don't have data of your own yet. We do the ingest, scoring, and building with you, so you get recommendations you can stand behind and a team behind them. IT stays the owner of your AI tools and works with us on setup. If you run RevOps or enablement and want the machinery first, start with Self-Learning Skills.
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.