The platforms behind our engineering.

Turn the control environment into a live evidence system.

ControlFrame connects evidence to its source, preserves lineage and chain of custody through signed manifests, maps requirements and crosswalks between frameworks, runs live control tests, and organizes the technical record so an assessor can work in it directly.

Capability scope

• Evidence collection with source lineage
• Cryptographic hashing and signing
• Requirement mapping and cross-framework crosswalks
• Live control testing
• Assessor and auditor workspaces

Train, evaluate, and sign the models that go into production.

LeanLogix connects model adaptation and training to evaluation design, data lineage, and release review. A release manifest binds the model and its evidence by digest; the signature supports integrity and signer verification. Reproducing a result also requires the workload, evaluator, configuration, and environment.

Capability scope

• Adapter-first training on open-weight bases
• Evaluation suites authored before training
• Separation of duties on promotion
• Model, dataset, and lineage records per release
• Signed releases with offline integrity checks

Put a gate between an agent's work and production.

The harness seals a verdict before code is allowed to ship. Policy runs at the boundary rather than inside the agent, the decision is recorded as an artifact, and an agent cannot grant itself the permission it was refused.

Capability scope

• Policy evaluated at the release boundary
• Sealed verdicts recorded as artifacts
• Agents cannot self-authorize
• Replayable decision records
• Vendor-neutral across coding agents

Connect an evaluation to the deployment that produced it.

MOEModels provides experimental tools for planning, running, verifying, and gating evaluations of a specific model deployment. Evidence passports connect the endpoint, workload, configuration, and recorded results so an engineer can inspect the conditions behind an evaluation.

Capability scope

• Deployment planning and endpoint measurement
• Evaluation run records and evidence passports
• Evidence verification and policy gates
• Evaluation tooling under Apache-2.0

Put governed AI on the healthcare operating path.

HealthNext Runtime combines a governed workflow runtime, typed system tools, privacy boundaries, human decision gates, audit records, and payer accelerators across prior authorization, claims, appeals, and member operations.

Capability scope

• Governed agentic workflows
• Typed tools against systems of record
• Privacy and human-authority boundaries
• Prior authorization, claims, and voice accelerators
• Signed, independently verifiable records

Connect the operating signal to an accountable decision.

LockedIn Labs AI Ops brings network and contact-center observability, AI agent orchestration, investigation and governed decisions into a shared operating context. Explore the platform overview and field notes by Sam M. Sweilem, then sign in to evaluate the synthetic reference workflows.

Capability scope

• Service topology and operational evidence
• Network and contact-center operating views
• Agent orchestration and investigation
• Decision ownership and approval records
• Public AI operations field notes