Industries
Technology
Product teams embedding AI into their own software, and engineering orgs adopting coding agents.
Technology
Where AI pays
- Embedding AI into your own product, where the engineering bar is the same as the rest of it.
- Engineering productivity, where coding assistance is already in use but ungoverned.
- Customer support deflection across documentation and prior tickets.
- Internal knowledge for teams that have outgrown their own wiki.
Technology
Common use cases
- Ship an assistant inside your product, grounded in customer-specific data with tenant isolation.
- Review generated code against your standards before it reaches a human reviewer.
- Resolve support tickets from documentation, escalating with the context already assembled.
- Answer engineering questions from the codebase, ADRs and incident history.
Technology
What constrains it
- Multi-tenant isolation: one customer's data must never surface in another's answers.
- Cost per inference becomes a unit-economics question once it is in the product.
- Provenance of AI-generated code matters for licence exposure at exit or audit.
Related capabilities
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Production AI applications built for your business, not configured from a template.
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Coding agents, automated testing and AI-assisted delivery applied inside a real review process.
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Dedicated AI Teams
Long-term AI engineering capacity built around your stack, your standards and your delivery model.
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Product teams embedding AI into their own software, and engineering orgs adopting coding agents.