AI Agents for Product Management

Know what to build, and who's asking.

Ranked needs sized by revenue. Evidence at every release gate. Proof that what you shipped is being used. Three agents reading your own calls, tickets, surveys and product data — inside your environment, with a person approving every output.

Book a working session See the agents

Under two weeks from kickoff to a working agent on your data.

The problem

Everyone has an opinion about the roadmap.

Sales has the deal that slipped. Support has the ticket volume. Someone on the exec team had dinner with a customer last week. All of it is real, and none of it tells you which accounts asked for what, or how much revenue is waiting on it.

The answers already exist. They are in call recordings, support cases, survey responses, the ideas portal, and the messages the field sends you. Reading all of it, every week, and tying each comment back to an account is a job nobody has time for — so the loudest input wins by default.

The roadmap doesn't fail for lack of feedback. It fails because nobody can read it all in time.

Agents

Three agents, three questions you answer every quarter

Inbound

Voice of Customer Agent

“What should we build next, and who is asking for it?”

  • Reads every call, ticket, survey response and ideas-portal entry, daily
  • Groups them into needs by product area, topic, sentiment and urgency
  • Ties each one to the person, the account and the parent company behind it
  • Ranks by the revenue asking, not by how many times something came up

Approved needs land in your backlog with the original quotes attached, so the case is already made the next time someone asks why this one is above that one.

Adoption

Product Adoption Agent

“Is what we shipped actually being used?”

  • Readouts at 30, 60 and 90 days on every launch
  • Which behaviors separate the customers who stick from the ones who stall
  • Who is stuck in setup, and the step where they stopped
  • Which accounts are growing, which are lapsing, and the reason for each

What it learns goes back to the Voice of Customer Agent as new needs. That closes the loop between what you shipped and what you build next.

Launch

Go-to-Market Agent

“Is this release ready to go?”

  • Finds beta-fit customers and drafts the ask
  • Tracks how beta partners actually use it, not just whether they replied
  • Writes the go or no-go brief with the evidence behind it
  • Drafts the release notes, the announcement and the FAQs

The gate decision arrives with its evidence attached, so the review is a conversation about the call rather than a scramble to assemble the slides.

In the workflow

It shows up where you already work

Your backlog

Approved needs arrive as tickets, with the customer quotes and the revenue behind them attached.

Slack or Teams

A theme is growing. An account went quiet after the launch. A competitor came up in three calls this week.

The review queue

One screen where your team confirms, edits or rejects what the agent found, before any of it moves.

There is no new system to live in. The only purpose-built screen is the one where your team approves what an agent produced.

4+ hours

saved per person each week

Under 2 weeks

kickoff to a working agent

Every need

sized by the revenue asking

Guardrails

What it will not do

It will not contact a customer. Every survey and every note is a draft until a named person approves it.

It will not hand you a number you cannot trace. Each count links back to the calls, tickets and quotes underneath it.

It will not treat volume as importance. Ten complaints from one account count once.

It will not leave your environment. Your cloud, your data, and whichever model your security team has approved.

Other teams

The same agents, asked different questions

Product Marketing

Launch readiness backed by evidence, and positioning drawn from your customers’ own language.

Read more

Customer Success

Which accounts are getting value, which are stalling, and what the renewal conversation needs.

Read more

Product Operations

Tag coverage, naming, segments and access, checked on a schedule instead of before a board meeting.

Read more

See it working on your own feedback

Bring a month of calls, tickets and surveys. We will show you the needs the agent surfaces, ranked by the revenue behind each one, with the quotes attached.

Book a working session All Product Success Agents

FAQ

Common questions

Does this replace our product analytics?

No. Product analytics tells you what people did. These agents add why, by reading the calls, tickets and surveys alongside the usage data and tying every need back to the accounts asking.

How does it decide what matters most?

By the accounts asking and the revenue behind them, not by how many times something was mentioned. Ten complaints from one customer count once.

Do we need Pendo for this?

Not for the Voice of Customer Agent, which works with any call, ticket and survey data. The Product Adoption Agent needs product usage data, and Pendo is the most common source.

Will it write to our backlog on its own?

Only after someone approves it. Needs land in a review queue first. Once your team confirms one, it flows into the backlog with the original quotes attached.

How long before a product team is using this?

Under two weeks from kickoff to a working agent on your own data. A pod stays with your team after that until it is in weekly use.