Governance
You Can't Trust What You Can't Govern
Your agent answered. But did it follow the rules?
Set cost, quality and risk boundaries for AI apps and agents, flag risks, and route issues for review. Build accountability with evidence behind every decision.
No credit card required to start. 5-minute set up.
Built for .NET, Python, and JavaScript teams.
Control Access, Spend and Risk Before AI Apps and Agents Scale.
Set operating boundaries before AI apps and agents run, then prove what happened after.
Set the Rules. Govern Model, Tool and Spend access.
- Define boundaries for models, tools, context and spend.
- Manage approved model access, keys, tools, and cost controls before runs.
- Connect policy signals to owners, environments and traces.
Model Gateway is available for Pro and Custom plans and priced separately.
Catch Risky Behavior Fast. Escalate What Matters
- Detect AI risks including hallucinations, poor grounding, unsafe outputs, and PII exposure.
- Monitor safety, quality, cost, and performance in production.
- Alert owners when thresholds are crossed or policies are violated.
- Escalate sensitive interactions for human review with full execution context.
Prove What Happened. Build Accountability.
- Preserve prompts, model calls, tools, context, costs, verdicts, and review decisions.
- Trace outputs, actions, approvals, and escalations to their source.
- Support audits, compliance reviews, and investigations with trace-connected evidence.
- Feed findings back into policies, approvals, and evaluations.
Capabilities
Control and Evidence for Accountable AI
Agent and LLM App Policies
Set boundaries for cost, quality, safety, security, models, tools and context.
Auditing
Keep trace-connected records for reviews, investigations and governance.
Human Review
Escalate sensitive, risky or low-confidence runs with full run context preserved.
Model Gateway
Control approved model access, keys, regions and usage policies.
Pro and Custom plans; priced separately.
Alerts & Notifications
Notify the right owners when behavior crosses cost, quality, safety or latency thresholds.
Cost & Usage Controls
Attribute token usage and estimated cost to agents, workflows, models, and owners.
AI Improvement Loop
Build Trust Through Continuous Oversight
Design with Control. Observe what happened. Evaluate the outcome. Improve continuously.
Trace Your First AI Agent in Minutes
Use the agent skills or instrument manually to start capturing traces.
Sign up for free · No credit card required
Copy and paste this prompt:
Install https://github.com/telerik/observability-skillsWorks with Cursor, Claude Code, Copilot, Codex and more.
Set up API Key
Your agent will ask for your API key. Get your API Key here.
Learn & Explore More
Pricing
Simple, predictable pricing. Start free, scale as you grow. No surprises, no hidden fees.
Free ForeverFor developers testing early agent prototypes
per month
Includes 10,000 units
Retention: 7 days
StarterFor small teams deploying their first live AI agents
per month
Includes 200,000 units
Retention: 30 days
$8 USD per additional 100K units
ProFor teams running production AI agents at scale
per month
Includes 1,000,000 units
Retention: 60 days
$8 USD per additional 100K units
EnterpriseFor organizations scaling governed AI applications
per month
Custom trace volume
Retention: Infinite
Explore More in Progress Agent Engineering
Observability
Observe and debug production behavior
Trace prompts, model calls, retrieval, tools, workflow steps, latency, tokens and cost so teams can understand what agents actually did.
Evaluations
Design, Test and Improve Agent Behavior
Use prompts, playgrounds, datasets, experiments and LLM-as-a-judge evaluations to compare behavior before and after release, track regressions and optimize for quality, safety and cost.
Memory & Context
Control What Agents Retrieve, Remember and Reuse
Manage what agents retrieve, remember, reuse, share and forget across workflows so they use the right context in the right place.
Agent Engineering Overview
See the Full Control Layer for Production AI
Explore how Progress Agent Engineering brings observability, evaluations, governance and memory/context together to help teams improve quality, cost and trust in production AI.
Works with Your Stack
The Progress Agent Engineering Platform integrates with the tools, frameworks and platforms teams already use to build and run AI agents.
- Languages & SDKs: .NET (C#), Python, JavaScript/TypeScript
- Agent Frameworks: Semantic Kernel, LangChain, LlamaIndex, AutoGen, Microsoft Agent Framework
- LLM Providers: Azure OpenAI, OpenAI, Anthropic
- AI Tooling: Microsoft.Extensions.AI, Microsoft AI Foundry, Progress RAG
- Enterprise SSO: Okta, Azure AD, SAML
- Open-Source Models (OSS): Llama 2/3, Mistral, Mixtral, Falcon, Gemma, etc.
Run AI with Accountability
Set clear boundaries, manage risk, and build trust with evidence.