Product Success Agents
Your customers already told you.
Ship better products. Drive adoption. Prove value.
Agents for product, marketing, and customer success, turning your customers' own words into ranked needs sized by revenue. Running on your data in under two weeks.
In your team's daily workflow in weeks. Not another pilot that never ships.
Ship better products
Needs ranked by the accounts asking and the revenue behind them, with the original quotes attached.
Drive adoption
Launch readouts at 30, 60 and 90 days, and the behaviors most tied to retention.
Prove value
Every number links back to the calls and tickets behind it, on data you can trust.
The outcome that matters
AI your teams use every day
Enterprises get excited, launch a pilot, and watch it stall on messy data and teams that never change how they work. We are not finished when an agent works. We are finished when your team uses it without thinking about it.
88%
of AI proofs of concept never make it to wide deployment. For every 33 launched, four reach production.
IDC, research with Lenovo
That gap is the work
Pilots stall on data nobody trusts and workflows nobody changed. We fix the data first, put the agent where your team already works, and stay until it is in weekly use. Shipping into production is the engagement, not the demo.
Where your teams already work
Findings and drafts arrive in Slack, Teams, email and your backlog. Where the work needs its own screen, like approving what an agent produced, it is one purpose-built app, not another system to live in.
Used, and measured
We track how many people use the agents each week and report it, the same way we would any product.
We stay until it sticks
A pod runs the agents with your team, tunes them on real corrections, and only then hands them over.
The problem
The answers are already
in your data
Almost none of it reaches product in a form anyone trusts, and nobody can say which accounts are asking.
The data isn't the problem. The hours it takes to make sense of it are.
Agents
One agent for every stage
of the product lifecycle
Two foundation agents sit underneath the rest, because everything depends on clean data.
Inbound
Voice of Customer Agent
What do customers need, and how much revenue is asking?
Read moreLaunch
Go-to-Market Agent
Is this release ready, and is it landing?
Read moreAdoption
Product Adoption Agent
Who is getting value, who is stuck, and why?
Read moreFoundation
Pendo Audit Agent
Can we trust our product data?
Read moreFoundation
Center of Excellence Agent
Is the program running well?
Read moreHow it fits together
Agents read the systems you already run, and the work lands where your teams already are. Nothing reaches a customer without a person approving it.
Where you interact with the agents
Analytics
Dashboards and needs sized by revenue
Tailored apps
Purpose-built screens where your team reviews, edits and approves
Slack and Teams
Alerts and answers where your team already works
Email and your tools
Drafted notes, backlog entries, release content
Agents
Customer feedback is quantified, mapped to customer segments, and supported by verbatim quotes, calls, and tickets.
Signals from your data sets
Delivery and staffing
Embedded until the agents work
Enterprise AI fails in the last mile, where agents meet messy data and teams that don't trust the output. A pod stays inside your business until the agents hit agreed targets.
The pod
Agent Engineer
Connectors, identity resolution and the agent pipeline.
Full timeDeployment Strategist
The business outcome, and how teams work once agents are live.
Full time or half timeEngagement Lead
Stakeholders, access and the roadmap.
Part timeEngineers can sit offshore with an onshore Balboa lead behind them.
Where we start, and what follows
-
1
Way in
Pendo Audit AgentHealth baseline in days
-
2
First build
Voice of Customer AgentBiggest pain, fastest proof
-
3
Next
Product Adoption AgentIs what shipped being used
-
4
Next
Go-to-Market AgentEvidence at every gate
-
5
Ongoing
Center of Excellence AgentKeeps the program running
Design, build, operate, transfer
Design
Map sources, categories and approvals
Build
Stand it up, test on labeled real feedback
Operate
Run it, tune it, report accuracy monthly
Transfer
Your team owns it, documented
How it is priced
First build
Fixed fee, typically a 120-day Use Case Accelerator.
Ongoing
Monthly retainer on allocated headcount.
Voice of Customer Agent
Hear every customer.
Act on what matters.
Ties every comment to the account and revenue behind it, and turns it into ranked needs product will trust.
Capture
Every source daily, long calls split so nothing is lost
Understand
Sorted by area, topic, sentiment and urgency
Attribute
Tied to the person, account and parent company
Size
Ranked by accounts, revenue and growth
4+ hours
saved per person each week
Under 2 weeks
kickoff to a working agent
Every need
sized by revenue
- Drafts a survey when a theme is growing, and finds who to ask
- Tracks who asked, and drafts the note when it ships
- Flags competitor mentions sized by spend
Your team confirms in a review queue. Approved needs flow into your backlog with the quotes attached.
Sources it reads
Go-to-Market Agent
Evidence at every release gate.
Most launches go out on gut feel and a date. This one runs on evidence.
Recruit
Finds beta-fit customers and drafts the ask
Learn
Tracks partners, reviews replays, watches funnels
Decide
Writes the go or no-go brief with the evidence
Launch
Drafts announcements, notes, one-pagers and FAQs
Product Adoption Agent
Turn launches into lasting usage.
Shipping is the halfway point. This agent finds what separates customers who stick from those who stall.
For your teams
- Maps product use and drafts the expansion note
- Scores growth and lapse risk, and explains why
- Ties behaviors to retention and recommends each fix
- Produces the 30, 60 and 90 day launch readouts
For your customers
- Walks new users to their first win, then hands off
- Answers how-to questions from your help content
- Nudges back users who stall during setup
What it learns returns to the Voice of Customer Agent as new needs. That closes the loop.
Pendo Audit Agent
Clean data before anything else.
Every agent is only as good as the data under it. This one tells you what to fix. Baseline in days.
Tag coverage
WeeklyUntagged pages, broken tags, untagged releases
Account identity
MonthlySub-accounts that don't roll up, bad metadata
Naming and duplicates
MonthlyOff-standard names, duplicate pages and events
Stale content
MonthlyNothing in 90 days, unused drafts, expired guides
Segments
MonthlyUnverified, unused, or built on bad data
Access
MonthlyRoles, admin rights, people who left
Install health
MonthlyPendo on every app, integrations passing
Center of Excellence Agent
The audit finds the problems.
This agent gets them fixed.
Product data programs fall apart when nobody owns them. This one keeps yours running.
- Gives every audit finding an owner and a due date
- Sizes requests and routes them to the right builder
- Checks scheduled in-app messages across teams
- Sets the standards for tags, names, surveys and guides
- Reconciles numbers when two tools disagree
- Writes the leadership summary
Anyone can ask it plain questions and get a chart back.
Principles
How our agents work
Tailored to your business
Shaped around your products, segments and decisions.
Inside your IT environment
Your cloud, your data, your approved model.
People decide
Agents draft. A named person approves.
Every number shows its work
Each count links to the quotes behind it.
Revenue counts, not volume
Ten complaints from one customer count once.
Built to be handed over
Our goal is a team that runs these agents without us.
Why Balboa
Why we build these
Product analytics is one input. Calls, tickets, surveys and frontline feedback are the rest, and that's where the signal lives.
We change the way product companies work and make it better.
See it working on your own feedback
Bring a month of calls, tickets and surveys. We'll show you what the agent surfaces and the revenue behind each need.