Your customers expect AI in the product and your team expects it in their tools. The path covers both: features users pay for and an engineering process that ships faster.
Assistants that answer from the customer's own data and take actions inside your product.
Answers drawn from your docs and tickets, with hand-off to a person when confidence is low.
AI-assisted coding, review and testing built into the way your team already works.
Four stages, each ending with a decision. The first line of every stage is specific to your industry.
Use case scoring
12 assessedOwner: Head of product
Measure: weekly active copilot users
Pilot: in-product copilots
Week 448/50 evals passed
Tickets answered by the copilot
Decision: continue
Reviewed with the owner
Connected systems
AI use cases
This quarter41% of tickets
Answered without an agent
Software buyers now expect AI inside the product, not beside it. We add engineers who work in your codebase and release cycle, from the first MVP to a multi-tenant platform with agents, copilots and usage-based billing.
Tell us about your business and where the time goes. We will come back with the use cases we would assess first and how we would test them.
