The evidence layer for enterprise AI adoption

Decide where AI goes. With evidence.

Capolla observes how work actually happens — on the device, with consent1 — and turns it into two answers: where AI will save time, and where it is already being used without review. Raw data stays local.2

Raw data stays local by default
Never stores what you type
Off until explicitly started
Observes and reports — never blocks
Capolla Daily Review dashboard showing hour-by-hour work summaries, recoverable time, and evidence strength for a pilot team
01 The problem

Every AI plan is built on someone's guess.

Boards are demanding AI strategies with numbers attached. But the numbers on offer come from surveys, where people describe their work as they remember it, or from consultants, who interview a sample for a week and extrapolate at engagement prices.

The tools that do produce real behavioral data — monitoring suites — get it by shipping screenshots and activity logs to the cloud. Employees notice. Behavior warps under observation, trust erodes, and the data quality collapses with it.

The result: companies decide where to put AI based on the least reliable evidence in the building.

Evidence collected adversarially is bad evidence. People change how they work when they're watched by something they don't trust.
Why Capolla is local-first by design
02 What the evidence looks like

A report your leadership can interrogate.

Thirty days of observed workflow evidence, condensed to the decisions that matter: which repeated workflows are worth automating first, how much time is recoverable,3 and which AI tools have already entered your workflows unreviewed. Every number is traceable back to the timeline it came from — nothing in the report is "the AI says so." The evidence sits one click behind each recommendation.

Capolla Overview timeline showing activity density, visible events, screenshots, and active apps observed across a workday

Figure 1. The Overview timeline behind a pilot report — every event is timestamped, app-tagged, and traceable back to the moment it happened.

03 The method

Observed, not asked. Local, not uploaded.

i.

Deploy locally

A desktop agent and dashboard install on pilot machines. Capture is off until explicitly started, the default profile is minimal, and recording status is always visible in the tray.

ii.

Collect on the device

Structured events — app and window changes, activity bursts, optional context — accumulate in a local database. Nothing uploads automatically; employees can inspect their own timeline.

iii.

Review, then decide

The dashboard ranks automation opportunities by estimated hours and surfaces AI usage for human review. External AI analysis requires compile, preview, and explicit consent — audited per send.2

04 What it never does

Written for the people being observed.

Capolla only works if the people it observes can trust it, so its guarantees are structural — properties of the architecture, not lines in a policy document. This section is meant for your employees, your works council, and your DPO as much as for the buyer.

Never stores what you type

Typing is captured as burst timing only — when it started, stopped, how long it lasted. Characters are never persisted. There is no keylog to leak.

Never uploads automatically

Raw capture data lives in a local database on the device. There is no background sync of events or screenshots to anyone's cloud, including ours.

Never records invisibly

Capture is off until explicitly started and its status is visible in the system tray. There is no stealth mode, and we won't build one.

Never blocks or enforces

Capolla observes and reports. Governance findings go to a human review queue — it never kills a process or interrupts anyone's work.

SignalWhat is actually recordedPilot default
App & window changesForeground application and window title, and when it changed.ON
Pointer & scroll activityCoalesced activity bursts — the shape of activity, not a cursor recording.ON
Typing burstsStart, end, and duration only. Never the characters.OFF
ScreenshotsRate-limited, automatically redacted (best-effort),4 stored on-device only.OFF
Clipboard eventsThat a copy happened, and between which applications — never the contents.OFF
Typed charactersNEVER
Raw OCR transcriptsScreen text is scanned once for redaction, then discarded.NEVER
05 The pilot

Thirty days from install to a defensible plan.

1Week 0

Scope and setup

Pick the pilot team, agree the capture profile with IT and privacy stakeholders, and roll out the employee communication kit before anything records.

2Weeks 1–3

Evidence collection

Capture runs in the agreed profile, locally on each machine. A mid-pilot check-in confirms signal quality.

3Week 4

Report and walkthrough

We present the AI Opportunity Map, the Shadow-AI Governance Report, and the top three automation moves — with the evidence behind every number.

4After

Continue, or stop cleanly

Expand to an annual rollout, or uninstall. Either way, the local data is yours to keep or destroy — we never held it.

30-Day Pilot

Priced like the assessment it replaces, not like seat licenses. Converts to an annual per-seat plan if you continue — pilot fee credited.

Request the pilot

No spam, no drip campaign. A personal reply within two business days.

  • AI Opportunity Map, ranked by estimated hours3
  • Shadow-AI Governance Report with review-queue findings
  • Employee communication kit and privacy summary for DPO review
  • Executive walkthrough with the raw evidence on hand

Notes & claims

  1. Capture is off until explicitly started; the packaged pilot default is the minimal profile, and recording status is visible on every machine. Covert deployment is not supported, by design.
  2. Raw capture data stays local by default. External AI analysis is opt-in per send: compiled, previewed, explicitly consented to, and logged with full request payload, response, and token usage.
  3. Time-savings figures are estimates derived from observed workflow evidence, not guarantees. Each estimate carries an evidence-strength rating and links to its underlying timeline.
  4. On-screen redaction of emails, card numbers, and other sensitive content is automatic and best-effort; it can miss or over-redact. This is one reason screenshots are off by default.
Capolla pilot

Request the pilot

Tell us a little about your team and we’ll prepare a focused 30-day pilot conversation.