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Define the product contract
We specify what the feature may read, which actions it may take, when it must ask for confirmation, and how the user can recover from a mistake.
Industry · SaaS
We help SaaS teams ship AI features their customers actually use — onboarding agents, in-product copilots, churn predictors, and revenue-side automation.
RAG over your own docs, schemas, and customer data — answers your support team would give.
Walk new users through setup with context on their actual workspace.
Predict and explain churn risk, then route at-risk accounts to the right play.
Auto-research accounts, draft outbound, brief reps before every call.
Activation lift on AI onboarding
Tickets deflected per dollar spent
Median feature build → ship
Implementation guide
The strongest SaaS AI features sit inside an existing customer workflow and improve a metric the product team already owns. We start with the job users are trying to finish, the private context the system needs, and the action it must take. Only then do we choose between retrieval, an agent, a predictive model, or a simpler deterministic feature.
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We specify what the feature may read, which actions it may take, when it must ask for confirmation, and how the user can recover from a mistake.
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Real examples become repeatable tests for usefulness, groundedness, tool accuracy, latency, and cost before the feature reaches customers.
03
Feature flags, cohort comparisons, feedback capture, and trace-level observability show whether activation, retention, or operator throughput actually improves.
Engagement
We’ll spend a focused week mapping your highest-leverage AI workloads and write you an honest memo.
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