Product Success Agents
AI teammates for product and customer success
Balboa is a product operations team that has helped over 250 B2B product companies spot customer needs, launch successful products, and activate customer usage.
The outcome that matters
Change the way your team works
Most AI projects automate what a team already does, and the team carries on working the same way, slightly faster. We use agents to change the method itself — how work gets decided, prioritized and done.
88%
of AI proofs of concept never reach wide deployment.
IDC, research with Lenovo
Reimagine, don't automate
We start from how the work should be done, not the steps your team runs today.
New methods, deployed
Each agent reinforces new ways of working: what gets reviewed, decided, and by whom.
Guided adoption
A pod stays until the new way is the normal way, then hands it over.
How it works
AI agents deployed in your environment
We deploy into your cloud, on your data, with your company's approved agents and models.
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
One shared record, four teammates. Each works the same evidence and answers the questions its team actually asks.
Company Brain
Unified customer record
People, accounts and parent companies resolved into one identity.
Shared definitions
One meaning for active, at risk and adopted, used by every agent.
Shared memory
Customer history, interactions, and intelligent summaries.
Your data, resolved once and shared. Every agent reads the same brain, so two of them cannot disagree about the facts.
Signals from your data sets
Delivery and staffing
How we work
Enterprise AI fails in the last mile, where agents meet messy data and teams that never changed how they work. We start small enough to prove it in a month, then stay as long as the work needs us.
Engagement model
30-day POC
An agent design sprint: clickable prototypes, workflow designs, an architecture plan, a data source analysis, and build prompts.
Agent Accelerator
90 to 120 days. Build the agents, wire the connectors, and get the output into the tools your team already uses.
Ongoing agent operations
An extension of your ops team, making sure your agents produce valuable and accurate work every day — quality, guardrails, evals, edge cases and escalation.
The pod
Forward Deployed Operator
Runs the agents alongside your team day to day, works the review queue, and feeds corrections back.
AI Deployment Strategist
The business outcome, and how your teams work once the agents are live.
Forward Deployed Engineer
Connectors, identity resolution and the agent pipeline.
Engineers can sit offshore with an onshore Balboa lead behind them.
30-day agent POC
Words are cheap. We’ll show you — we build your first agent together before you commit.