What sits between a language model and an answer you can act on.
A team can connect a language model to its data and tools directly. Getting from there to answers people can verify and actions they can trace takes several further parts. Corlogic provides those parts and configures them with your team.
Full control, and full ownership.
Building in-house gives full control over every component. It suits organizations with platform engineers who can maintain what they build.
Seven parts beyond the model.
- A governed model of business definitions, validated against the data. In Corlogic this is StarEngine.
- A query path that does not let the model invent joins or calculations. Corlogic compiles exact, read-only SQL deterministically.
- Access control down to the row, and a least-privilege role for queries.
- A way to keep sensitive values inside the controlled environment. Corlogic's privacy gateway tokenizes them before an external model call.
- A process runtime that keeps state through approvals, timers, retries and exceptions.
- Limits on each AI agent: its instructions, model, tools and output.
- Audit and observability across the whole path.
Engineers who work on your problem.
Corlogic's engineers work with business and technology teams to connect the systems, build the model around how the business works and configure the monitored conditions, triggers, actions, permissions and approval rules. This is forward-deployed engineering.
Corlogic supports selected external model providers and compatible self-hosted endpoints.
Where is the team's time best spent?
The question is less whether a team could build these parts than whether building them is the best use of its time. Starting with one real operating problem shows quickly what the first application needs.
How We WorkStart with a recurring process that is harder to coordinate than it should be.
Talk to us about where context gets lost, decisions stall, or follow-up breaks down across people and systems.
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