Enterprise knowledge and search
Grounded assistants that find, synthesize, and cite information from approved business sources.
Applied AI systems
Put AI to work
inside your business.
We connect models to approved data, tools, and workflows, then build the evaluation, security, and operating layers that turn a promising prototype into dependable capability.
Frame
Ground
Integrate
Improve
What we build
AI systems designed around real work.
Start with the decision or task that matters, then use the smallest effective combination of models, retrieval, tools, and human review.
Tool-using agents
Workflow agents that take bounded actions across business systems with explicit permissions and human approvals.
Role-specific copilots
Focused interfaces that help teams draft, analyze, decide, and move work forward.
Evaluation and AI operations
Repeatable tests, guardrails, telemetry, and cost controls that make quality visible after launch.
How we work
Prove value before adding complexity.
The work moves from a measurable use case to a production system through short, evidence-driven stages.
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01
Frame
Define the users, task, data boundaries, risks, and a useful measure of success.
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02
Prototype
Test the workflow with representative data and expose weak assumptions early.
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03
Productionize
Integrate identity, permissions, tools, evaluation, monitoring, and human escalation.
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04
Improve
Measure real usage, review failure modes, and tune the system against changing needs.
Built for operation
Useful AI is an operated system, not a demo.
Model choice is only one part of the solution. The surrounding controls determine whether people can trust it with meaningful work.
- Grounded in approved sources
- Permission-aware by default
- Measured against real tasks
- Recoverable when confidence is low
Evaluation scorecard
Source coverageVisible
Task successEvaluated
Escalation pathDefined
Cost and latencyObserved
What you receive
A working system and the evidence behind it.
Artifacts are tailored to the engagement, with enough context for your team to own what comes next.
01Use-case and risk brief
02Data and integration map
03Working prototype and evaluation suite
04Deployment and monitoring plan
Technology in context
Choose technology after the workflow is clear.
We select components for required quality, privacy, latency, and economics—not for a logo wall.
Models
- OpenAI and Azure OpenAI
- Gemini and other fit-for-purpose models
- Model routing and structured output
Orchestration
- Retrieval and knowledge grounding
- Tool use and workflow state
- Human approval and escalation
Operations
- Evaluation and guardrails
- Telemetry and feedback loops
- Latency and cost controls
Selected tools and platforms
Representative technologies we work with, selected according to project fit.
OpenAI
Google Gemini
LangChain
Microsoft AutoGen
Microsoft Copilot
Start with the work