Runtime control infrastructure for generative AI.
Assiduity provides runtime control infrastructure for generative AI systems that need to stay aligned, observable, and governable during long-form and agentic workflows — without retraining or replacing the underlying model.
The runtime control layer ships as infrastructure, not a model replacement.
Assiduity is designed to sit between enterprise applications and model endpoints. It gives teams a practical way to evaluate runtime control, inspect generation behavior, and produce structured evidence without changing model weights.
SDK
Add runtime control to application workflows and define operating contracts for long-form or agentic tasks.
OpenAI-compatible proxy
Route generation through a provider-agnostic control layer while preserving familiar API patterns.
Dashboard
Review runs, baseline comparisons, constraint behavior, ε telemetry, and governance signals in one place.
Evidence export
Produce structured records that support technical review, monitoring, governance, and diligence.
Designed to fit the enterprise AI stack.
Assiduity is built for evaluation in existing AI workflows. In common SDK or proxy deployments, teams can begin review with a minimal endpoint or configuration change rather than a model migration.
One endpoint path
Evaluate runtime control by routing calls through the Assiduity layer rather than rebuilding the workflow.
No retraining
Control is applied at inference time, so teams can evaluate behavior without modifying model weights.
Provider-agnostic
Designed to sit above hosted, open, or private model endpoints instead of depending on one provider.
Control is applied during generation, not after failure.
Assiduity’s core technology, Equilibrium-Constrained DecodingTM, evaluates candidate continuations against a semantic operating contract while the model is generating.
Declare the operating contract
Specify required concepts, source facts, prohibited terms, policy boundaries, task constraints, and workflow expectations.
Route generation through control
Candidate continuations are scored against the contract before small deviations compound across the rest of the output.
Review telemetry and evidence
Each run produces structured records of constraint behavior, ε trajectory, branching activity, stop reasons, and governance status.
The product shows how the system behaved.
Final output is not enough for serious enterprise review. Assiduity records the generation path so teams can inspect whether the system remained aligned with the operating contract while it worked.
ε trajectory
Track deviation from the operating contract across the generation path.
Constraint behavior
Review whether required concepts were covered, prohibited terms were avoided, and task expectations were maintained.
Branching decisions
See when the controller evaluated alternatives and which continuation was selected.
Stop reasons and governance status
Preserve completion signals, pass/fail checks, and run-level governance summaries for review.
Control budget where drift risk is highest.
Runtime control does not need to mean applying maximum branching at every step. Assiduity can concentrate control where the generation path shows higher drift risk, reducing unnecessary candidate generation while preserving measurable control benefit.
The practical objective is not to replace stronger models in every case. It is to improve the operating reliability of model workflows — including smaller or lower-cost models — where long-horizon drift creates avoidable review, rework, or governance burden.
Where the product is designed to be tested.
The homepage shows industry consequences. The product page focuses on the workflow patterns where runtime control can be evaluated directly.
Long-form analysis
Evaluate whether extended summaries, research syntheses, and policy analyses stay tied to the original objective.
Agentic workflows
Review task alignment across multi-step workflows where drift can accumulate through tool calls and intermediate decisions.
Regulated work
Produce structured telemetry that can support monitoring, review, governance, and controlled technical evaluation.
Model governance
Give reviewers more than a final answer by exposing runtime behavior and constraint signals.
See the control layer in action.
The protected demo shows baseline generation compared with ECD-controlled output, including constraint satisfaction, ε telemetry, branching behavior, and governance records.
Ready to evaluate runtime control?
Assiduity is available for controlled review with selected enterprise teams, design partners, researchers, and prospective investors.