Enterprise context sits at the core, connecting field data with our delivery agents. Every project makes the next one better.
01 / ENTERPRISE CONTEXT
What it takes to understand a business is scattered across systems, documents and daily records. We connect it into each company’s own context: shared terms, clear workflows, structured know-how and evaluation criteria.
Give your data business meaning.
A customer, an order or a revenue metric can mean different things across teams and systems. Starting from real tasks, we define the objects, relationships and metrics behind one shared business language.
Understand how work and decisions unfold.
Real work crosses systems, teams and human decisions. From interviews, observation and past tasks, we map the full path from input to outcome, exceptions included, so agents get a clear role.
Turn individual expertise into shared know-how.
Policies set the rules; experts know why. We link SOPs, domain knowledge and past cases to real business situations, making tacit judgment explicit and reusable.
Define success on your own business terms.
Every company has its own bar for accuracy, compliance and quality. We turn real tasks, edge cases and expert judgment into a dedicated eval set, the shared yardstick for Build and Evolve.
02 / DELIVERY AGENTS
Four delivery agents build and maintain your enterprise context, then use it to ship the business agents your teams rely on.
Build business understanding from the work itself.
Turn interviews, recordings, documents, images, video and chat into structured field information. Expert experience helps spot gaps and guide follow-up questions.
Map the workflow. Find where AI can make a difference.
Map roles, handoffs and decision rules from field findings to spot bottlenecks, coordination gaps and exceptions. Weigh value against feasibility to find where AI fits and set a product direction.
Turn business goals into agents ready to test and deploy.
Design agent workflows around enterprise context, combine tools and skills, then develop, test and deploy. Test sets built from real tasks check execution, handoffs and exceptions in a sandbox.
Learn from live use and keep improving.
Analyze live records and business outcomes to find failures and room for improvement, then turn them into eval cases. Regression checks validate each change, and findings flow back to Research, Discovery and Build.
Context compounds. Agents improve.
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