# Otis

> Infrastructure for continual product improvement

Act on the hidden signal in your agentic product.

Turn anonymized UI and agent traces into product opportunities. Connect your
coding agents and measure the outcomes.

## Focus your judgement on what matters. Act on opportunities immediately.

The page illustrates this with an example feed inside a product mockup. The
account, figures and insights below are illustrative, not real data.

Insights · Chats · Data — Acme · Production

- Agent harness optimization (seen Aug 12 – Aug 28): The agent misplaces
  components in 71% of layout calls — the tool sends no units.
  High confidence · 1,240 sessions · $12K conversion
- Product suggestion (seen Aug 01 – Aug 29): Translation requests grew 5× in a
  month — nothing in the product does it.
  Medium confidence · 1,140 sessions · $50K conversion
- AI cost and value (seen Aug 18 – Aug 29): 72% of token spend goes to free
  users active for over three months.
  High confidence · 1,847 users · $34K conversion
- Agents as users (seen Aug 10 – Aug 29): Agents chain three CLI commands into
  one you never built — a third of them fail.
  High confidence · 40 accounts · $22K churn at risk
- Retention and churn (seen Jul 30 – Aug 29): Week-one chat discovery lifts
  30-day retention 14% — onboarding never mentions it.
  High confidence · 2,100 users · $50K churn at risk
- Cross-surface friction (seen Aug 15 – Aug 29): Users ask chat to “mark all as
  read” — the UI control is on screen every time.
  High confidence · 340 users · $18K churn at risk

The last of these is shown opened.

TL;DR
- 340 of the 1,210 users who opened the inbox asked chat instead — the control
  was rendered and on screen in every one of those sessions.
- The detour costs 15 seconds against under a second for the control — and 20%
  of times cancel is hit before completion.
- They are not new users — 71% had been active for over a month, so this is
  unfamiliarity with the layout rather than with the product.
- Chat answers correctly every time — the request succeeds, which is why
  nothing in your error rates or support volume moves.

Who took the detour: new users 12% · power users 47% · account champions 41%
When the cancel happens: before any result 52% · part-way down the list 31% ·
at the confirm step 17%

What to do about it — proposed solutions to explore
1. Put the control where the eye already is. Users open chat from the lower
   right and scan left. The control sits top-left, outside that path. Mirror it
   into the list header. (Prototype)
2. Let chat teach the control. When chat handles something the UI already does,
   have it name the control in the reply. The detour then costs 15 seconds once
   instead of every time. (Explore fix)

## Compound your product learning.

- Cross-surface product intelligence: Otis analyzes users’ interactions with
  your AI product across every surface — UI, chat, agentic workflows, MCP and
  CLIs. Otis discovers what your customers need, both human and agent.
- Rigorous, actionable insights: Otis gives you stories, not dashboards. It
  suggests actions to fix issues, improve your agent, simplify your UI, and
  drive user value. You get to focus on decision-making, not data-gathering.
- Continual product eval and improvement: Otis watches every PR and experiment.
  It sees what works, and what doesn’t. This learning is private to your
  product, and compounds Otis’ understanding of your customers.

## Bring your taste. We’ve done the heavy lifting.

- Every product signal, integrated. Connect telemetry from every product
  surface with context from support tickets, forums, and call transcripts.
- Your dev stack, integrated. Otis connects to GitHub, and your tools for
  releases, experiments and evals.
- Privacy for your users. Always. The Otis SDK anonymizes and PII redacts all
  telemetry. Otis never records your user’s browser.
- Statistics, handled. Otis takes care of the statistical rigor, so you can
  trust the insights.
- Your product ledger. No-one else’s. Otis’ agentic memory builds a deep
  understanding of your priorities and product. It’s used to improve your
  product, never anyone else’s.
- Works where you are. Otis is for PMs and engineers. Get daily briefings in
  Slack, personalized to your role. Use Otis through your agents with MCP and
  skills.

## Start listening now.

- The features most likely to improve retention
- Which users to go talk to
- Where users see most friction
- Which users are getting most value
- What agent behavior predicts user churn

Learn more about Otis with one of our founding team.

© 2026 Ortelis Inc

## Links

- Book a demo: https://cal.com/team/runotis/otis-demo
- Josh Greene: https://www.linkedin.com/in/greenejoshua/
- Tim Moreton: https://www.linkedin.com/in/timmoreton/
- Amy Slawson: https://www.linkedin.com/in/amyslawson/
- Privacy: https://www.runotis.com/privacy
- Terms of service: https://www.runotis.com/terms