# 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.

[Book a demo](https://cal.com/team/runotis/otis-demo)

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

*The section below is the example feed shown inside the product illustration on
this page. The account, figures and insights 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

#### 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.

- [Josh Greene](https://www.linkedin.com/in/greenejoshua/)
- [Tim Moreton](https://www.linkedin.com/in/timmoreton/)
- [Amy Slawson](https://www.linkedin.com/in/amyslawson/)

[Book a demo](https://cal.com/team/runotis/otis-demo)

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