Generation-time control for enterprise AI

Aligned
Intelligence

Keep AI execution aligned with your operating mandate while it works.

Assiduity adds a control layer to the AI models you already use. It steers each generation toward your policies and evidence requirements and flags drift for human review—without replacing or retraining the model.

Evaluate a workflow See how it works

Keep your models · No retraining · Works across supported providers · Path-level evidence

assiduity /əˌsijooˈidədē/ constant care, attention, and persistence in the work at hand.

The delegation gap

The answer is not enough.

Consequential enterprise work involves choices under uncertainty. A model decides what matters, which evidence to rely on, what trade-offs to make, and when the work is complete.

Many paths can produce a plausible answer. Trust depends on whether the path the model chose remained valid under your operating mandate—and whether it escalated when machine judgment was no longer enough.

Consider a vendor-contract review: flag every non-standard indemnity clause, cite the source for each flag, and escalate liability above $5 million.

Uncontrolled output

8.1 Limitation of Liabilitycited
8.3 Mutual Indemnificationcited
9.2 Consequential Damagesno source cited
11.4 Uncapped Indemnitynot flagged

Fluent, well-formatted, confident. It looks complete—so it ships.

Governed execution

8.1 Limitation of Liabilitycited
8.3 Mutual Indemnificationcited
9.2 Consequential Damagessource cited
11.4 Uncapped Indemnitycited · human judgment required

Required issues surfaced. The unresolved liability judgment is returned to a person.

Plausible is not the same as governed. The uncontrolled answer violates evidence and escalation requirements even though it looks complete. Illustrative example, not a measured customer result.

Generation-time control

Govern the choices
while they are being made.

Assiduity sits between your application and the model endpoint. It keeps the operating mandate active, measures deviation as the path develops, and intervenes while alternatives remain.

Equilibrium-Constrained Decoding™ evaluates developing generation against the mandate and selects the path that best preserves the organization’s objective, policies, evidence requirements, and decision boundaries.

Assiduity does not make judgment deterministic. It keeps choices governed by the mandate, signals deviation, and returns consequential ambiguity to a person.

Application or agent

Assiduitygeneration-time control

Model endpointsupported provider

Explore the product See a controlled run

The governance advantage

Scale AI and human
oversight together.

Today, oversight is a headcount problem. Every output a human has to read is a cap on how much AI an organization can deploy. Assiduity emits a drift signal for every generation, giving teams a basis for directing review toward higher-drift work rather than treating every output alike.

Without a control signal

More AI output requires more human rereading.

Review capacity becomes the limit on deployment.

With generation-time control

Human attention can follow drift, ambiguity, and consequence.

People retain authority while the organization extends its operating mandate across more AI work.

Trusted delegation

What trusted delegation requires.

Trust does not come from assuming the machine is correct. It comes from governing its authority, choices, and evidence.

Mandate fidelity

Keep the objective, policies, evidence requirements, and completion standard active throughout the work.

Bounded delegation

Define where machine authority ends and unresolved choices must return to human judgment.

Reviewable execution

Return the work with evidence of deviation and control decisions—not merely the final answer.

Product system

Keep your models.
Add control.

Apply governance across supported models without replacing the application, retraining the model, or rebuilding the surrounding stack.

Proxy / API

Route supported model calls through an OpenAI-compatible control endpoint.

SDK

Integrate generation-time control into an application or agent workflow.

Dashboard

Compare baseline and controlled runs, inspect exceptions, and review the evidence.

Control telemetry

Track the ε trajectory, requirement coverage, candidate selection, branching, and stop reason.

Available for evaluation with one workflow, your existing model, and the requirements your organization already uses.

Applications

Where governed
judgment matters.

Start with work where several answers may be plausible, but the choices must remain faithful to an explicit mandate.

Controlled evaluation

Prove governance with
one workflow.

Compare baseline and controlled execution using the same model, task, sources, and operating mandate. Inspect both the finished work and how consequential choices were governed. Expand only where the governance result and operating economics justify it.

Define

Translate the task, evidence, authority, escalation, and completion requirements into an operating mandate.

Connect

Route the supported workflow through Assiduity while keeping the application and model in place.

Validate

Compare the output, drift trajectory, requirement coverage, candidate choices, and control record.

Expand

Extend control to additional workflows where the governance and economics meet the organization’s standard.

Evaluating Assiduity as an investor? Visit Company.

Managerial research

What AI Changes in Organizations and Markets

Seven working papers examine what happens when AI makes properties that historically traveled together independently variable—changing theories of project control, delegation, work design, brand choice, organizational learning, firm boundaries, and competitive advantage.

Explore the research program and available papers.

Insights

Latest thinking

Barbed Wire Defines the Edge, Not the Direction.

August 12, 2026

Move Fast.
Build Reliable^TM

Delegate more consequential work without surrendering the judgment, evidence, and escalation boundaries that make it governable.