AI product engineering
Design and build AI features inside real products, with clear boundaries between deterministic application logic and model-driven behavior.
Consensus Codeworks · AI-Backed Software
AI that earns its place in production.
We build software systems where AI is useful, measurable, and operationally accountable. Product engineering, data, evaluation, and support are treated as one delivery problem.
AI product engineering Agents and automation Data and MLOps Production support
Capabilities
More than a model behind an interface.
Useful AI depends on the surrounding software: data quality, integrations, access controls, evaluation, fallback behavior, and the ability to understand what happened in production.
Agents and workflow automation
Connect tools, data, and approval steps into guarded workflows that reduce manual effort without hiding decisions or operational risk.
Data and model operations
Prepare data flows, evaluations, monitoring, and release practices so AI behavior can be measured before and after deployment.
Platform integration
Integrate AI capabilities into existing web, mobile, cloud, and enterprise systems without forcing a full platform rewrite.
Delivery model
Control from first decision to live operation.
We can own an end-to-end workstream or join an existing team at a specific stage. In both cases, decisions and evidence remain visible.
- Frame
Define the decision and the guardrails
We identify the user outcome, data sources, failure modes, evaluation criteria, and the parts that should remain conventional software.
- Build
Ship a production-shaped system
Architecture, integrations, application code, prompts, tests, and observability evolve together from the first usable release.
- Prove
Evaluate quality and operational behavior
We test model outputs, cost, latency, security boundaries, fallbacks, and human review paths against explicit acceptance criteria.
- Operate
Improve with evidence
Monitoring, incident response, controlled releases, and ongoing evaluations make changes visible and reversible.
Good fit
Built for teams that need the system to last.
- A new product where AI is a core capability
- An existing platform that needs reliable AI features
- Internal workflows that require guarded automation
- Teams that need architecture, delivery, and operations support together
Start with the real constraint
