RUNTIME TRUST INFRASTRUCTURE

Build faster.Stay in control.Scale AI safely.

Knowent adds a runtime control layer around the AI and automation stack you already use. Move toward production faster while your policies, permissions, configured requirements, evidence and oversight stay connected to critical actions.

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Runtime control

Control at runtime

Context available

Configured policy evaluated

Permission evaluated

Controlled actionAction within configured scope

Controlled action

Evidence recorded

Action context and decision connected to evidence.

Context availableConfigured policy evaluatedPermission evaluated

ACROSS THE AI AND ENTERPRISE STACK

OpenAI
Azure OpenAI
Anthropic
Google Gemini
Amazon Bedrock
Mistral AI
Databricks
Snowflake
ServiceNow
Microsoft Entra ID
OpenTelemetry
Microsoft Sentinel
EU AI Act
DORA
ISO/IEC 42001
Human oversight
ACROSS THE AI AND ENTERPRISE STACK

KEEP YOUR STACK

Keep the tools your teams already use.Add control where AI becomes action.

Keep the developer tools, models, agents, workflows, APIs, data and enterprise systems you already use. Knowent adds an operating layer around the points where AI becomes action, without replacing your existing stack.

Keep model and agent choice open while the same operating rules stay around how they act.

WHAT STAYS

Models
Agents
Developer tools

KNOWENT OPERATIONALIZES

Authority boundaries
Permitted actions & tools
Governed routing
Evidence

RESULTAdd or change models and agents without rebuilding the surrounding operating model.

AS AI GAINS THE ABILITY TO ACT

Each stage adds context.

Models & Data
+ Permissions, Security & Policy
+ Risk, Configured Requirements & Evidence

Operating context

Keep context connected to action.

Context follows execution
Configured conditions are evaluated
Decisions stay linked to evidence

WHY NOW

AI is easy to build.Safe AI is hard to operationalize.

As AI moves from experimentation into production, it takes on more responsibility. The context around each action must grow with it.

Experimentation

Explore what AI can do.

Production

Put AI to work in real workflows.

Autonomous Action

Let AI act with less direct supervision.

BEFORE PRODUCTION

Turn requirements into an operating path before AI reaches production.

Knowent turns the policies, permissions, risk conditions and configured requirements you define into runtime controls before AI reaches production.

Control evaluation

01Internal policy

What has your organization defined?

Configured policies
Permissions
Your organization's controls

Action context, applied controls and decision retained.

Configured policies

What has your organization defined?

Action context, applied controls and decision retained.

ONE OPERATING LAYER

Give your AI workflows a shared operating foundation.

One operating layer for control, compliance, optimization, oversight and evidence across the AI stack you already use.

Runtime control
Keep AI actions within approved conditions as they happen.
Continuous compliance
Apply the policies and requirements your organization has configured while AI operates.
Cost & quality optimization
Keep model choice, cost, response time and quality in one operating context.
Human oversight
Bring the right person in when risk or policy requires it.
Evidence & traceability
Retain action context, applied controls and outcomes for review.
Reusable scale
Carry established controls across more models, workflows and teams.

WHEN AI ACTS

Automate what is ready. Bring people in when risk or policy requires it.

Your policies, permissions, risk conditions and runtime context determine whether an action executes automatically, needs approval, takes another route or stops.

Runtime decision

Requested action

Classify and route an incoming service request.

route_service_request

Runtime evaluation

{  "action": "route_service_request",  "authority": "within_permitted_scope",  "policy": "action_permitted",  "approval": "not_required",  "decision": "allow",  "evidence": "recorded"}

Authority evaluated
Workflow route eligible
Evidence requirement attached

RUNTIME DECISION

Allow action

EVIDENCE RECORDEDAction context, applied conditions and decision retained.

Requested action

Prepare a purchase that reaches an approval threshold.

prepare_purchase

Runtime evaluation

{  "action": "prepare_purchase",  "authority": "approval_required",  "risk": "approval_threshold_reached",  "execution": "wait_for_approval",  "decision": "require_approval",  "evidence": "recorded"}

Approval threshold evaluated
Human review required
Decision context attached

RUNTIME DECISION

Require approval

EVIDENCE RECORDEDPurchase context and approval requirement retained.

Requested action

Request access to data with additional handling requirements.

request_sensitive_access

Runtime evaluation

{  "action": "request_sensitive_access",  "scope": "sensitive_data_access",  "policy": "handling_condition_conflict",  "authority": "access_not_permitted",  "decision": "stop",  "evidence": "recorded"}

Data handling condition evaluated
Permission boundary checked
Policy conflict recorded

RUNTIME DECISION

Stop action

EVIDENCE RECORDEDAccess request, conflicting condition and decision retained.

Requested action

Choose an approved model or workflow for the task.

select_approved_route

Runtime evaluation

{  "action": "select_approved_route",  "eligibility": "approved_models_and_workflows",  "quality": "configured_requirement",  "cost": "configured_limit",  "decision": "select_eligible_route",  "evidence": "recorded"}

Model eligibility evaluated
Cost and quality conditions checked
Route decision recorded

RUNTIME DECISION

Select eligible route

EVIDENCE RECORDEDSelected route, evaluated conditions and decision retained.

REUSE AND SCALE

Reuse your operating model as AI expands.

Extend it across new workflows, models and teams as you scale.

Carry the model forward
Carry your policies, permissions and evidence into the next workflow.
Connect more of your stack
Add models, agents and systems to the same operating model.
Optimize in operation
Evaluate approved routes against cost, quality and operating conditions.
Scale with evidence
Expand across your workflows and teams while oversight and evidence stay connected.

THE SCALE GAP

Scale AI without multiplying complexity.

As AI spreads across your business, operating discipline, economics and evidence have to scale with it.

44%.
report enterprise-wide AI scaling
Reuse one operating model across your workflows instead of rebuilding it.
20%.
say operating costs have already constrained AI use
Keep model choice, route, cost and quality visible as you scale.
55%.
report a formal layer between AI and business use
Operating layers are becoming part of enterprise AI architecture.
12%.
consistently assess AI value against cost
Keep cost, quality and execution connected in production.

44%

report enterprise-wide AI scaling

Reuse one operating model across your workflows instead of rebuilding it.

20%

say operating costs have already constrained AI use

Keep model choice, route, cost and quality visible as you scale.

55%

report a formal layer between AI and business use

Operating layers are becoming part of enterprise AI architecture.

12%

consistently assess AI value against cost

Keep cost, quality and execution connected in production.

One operating model. More AI. Less fragmentation.

Knowent turns control, optimization and evidence into reusable runtime infrastructure.

START SMALL. SCALE FROM THERE.

Start with one workflow. Prove what works. Then expand.

Connect one meaningful workflow, establish the operating model around it, and reuse what works as your AI adoption grows.

One workflow

Start with a meaningful business process where AI creates real value.

Connect what you use

Bring the models, systems, data and workflows your teams already use into scope.

Prove in operation

Validate your operating model in real use before expanding.

Reuse and scale

Carry what works into more of your workflows, models and teams.

Turn one workflow into a repeatable path to scale.

See how Knowent can bring one of your real workflows onto a controlled operating path using your existing stack.

Book a demo

Build faster.Stay in control.Scale AI safely.

Control at runtime

Evidence recorded

Keep the tools your teams already use.Add control where AI becomes action.

Models & Agents

Data

APIs & Workflows

Enterprise Systems

Identity & Permissions

Each stage adds context.

Keep context connected to action.

AI is easy to build.Safe AI is hard to operationalize.

Experimentation

Production

Autonomous Action

Turn requirements into an operating path before AI reaches production.

Internal policy

Configured requirements

Risk, security & permissions

Runtime disposition & evidence

Runtime control

Continuous compliance

Cost & quality optimization

Human oversight

Evidence & traceability

Reusable scale

Classify and route an incoming service request.

Carry the model forward

Connect more of your stack

Optimize in operation

Scale with evidence

Scale AI without multiplying complexity.

Start with one workflow. Prove what works. Then expand.

One workflow

Connect what you use

Prove in operation

Reuse and scale