Realisier Labs

Where teams Adopt AI, Absorb it, and Advance with it.

  • Delivers weekly AI learning
  • Grounds every answer in your company's own knowledge
  • Charts each person's real AI usage: adoption you can watch grow
Bring Pulse to your team
Why we built Pulse

Hope is not an AI strategy. Numbers are.

Stop guessing your team's AI adoption: read it live, per person, per tool.

70%
of active time
45
people tracked
76h
AI time today
4
AI tools detected
Cortex adoption dashboard showing per-person AI usage: 70% of the team's active time runs on AI
Cortex: the team's AI adoption at a glance, updated live.
AI Tools Usage report showing time spent per AI tool (Claude, ChatGPT, Gemini, Codex) and per employee, with a downloadable report
Reports: which AI tools your team actually uses, and how much.
What we built

Making AI Work: From Learning to Adoption

Four things every AI rollout is missing, and Pulse does all four.

Weekly learning, built in

Weekly AI videos and assessments inside the app. Skills grow every week, and you can see who's learning and who's behind.

Answers from your own knowledge

Every question is answered from your company's own documents, not the model's general memory. No invented processes.

See exactly how much AI your team uses

Real AI time per person and per tool, measured from actual usage on their machines, not from what people say in a survey.

All models, costs under control

Claude, GPT and Gemini behind a single interface, with per-person budgets and the cost of every answer recorded.

Architecture

How the pieces fit

Workstation app Opt-in companion app measures AI-assisted time app-usage logs, batched Secure relay batches & forwards securely Web app Grounded Q&A + refinement loop adoption dashboards for leadership instant streamed answers Pulse backend auth · activity & time logs · AI sessions per-user provider routing · token quotas cost per response version fast · stores only what's needed Knowledge base 200+ small Markdown files retrieval picks relevant file(s) Cloud AI providers Claude GPT Gemini answers grounded in retrieved files Adoption database users · activity · tasks AI usage & quotas Activity store raw activity samples hourly & daily adoption rollups PHASE 2 · IN BUILD Processing queue → local model, private GPU scores AI effectiveness per user data never leaves our hardware samples relay questions context eval queue
Pulse: adoption signals flow up from opt-in companion apps, questions flow in from the web app, and one backend routes, grounds, meters and stores everything.
Built on trust

Employees see everything leadership sees

An enablement tool, not oversight: everyone sees their own numbers.

An employee's own dashboard: their day at a glance
Their own day at a glance, nothing hidden from them.
An employee's own activity view: the apps and AI tools they worked in across the day
Their activity: which apps and AI tools their day actually ran on.
Outcomes

What it changed

Our "AI transformation" is a number, not a slogan, and that's our proof to clients.

Restructured with evidence
The delivery team is restructured around AI-first workflows, with adoption data guiding where AI absorbs the work.
Answers people trust
Answers cite internal process docs instead of model memory. The knowledge base has been in continuous revision for 45+ days.
Adoption visible per person
Leadership sees each member's share of AI-assisted working time, with the team's consent and full visibility into their own data.
Costs metered per answer
Token quotas and per-version cost tracking mean nobody asks "what is AI costing us"; the dashboard already says.
Reliable under a full team
Hardened to stay fast and stable with everyone reporting in at once, so the adoption data never stops flowing.
A sovereignty path
Effectiveness scoring is moving to a locally hosted model on our own GPU server, so evaluations of people never leave our hardware.
Talk to Sachin

Want AI adoption you can measure?

Pulse was designed, built and is operated by Realisier Labs, on Realisier Labs. If you want your team's AI transformation to be a chart instead of a claim, let's talk.

Talk to Sachin