The pains
What breaks in the real world
Trust is broken
Client-facing agents are risky. One wrong answer can hurt your brand or break compliance.
The user always asks something new → hallucination
You hope your guardrails are enforced
RAG misses key facts under pressure
Going live takes forever
You reach 80% fast, then get stuck in endless tweaking. Better models won’t save you.
You can’t predict all user interactions
Every time you fix one bug, another pops up.
Prompt tuning is a Whac-A-Mole game.You’re debugging the agent like a script
LLMs evolve. Your agent should keep up
LLMs improve globally, but break locally.
We help your agent ride the wave, not drown in it.
Benefits
From infinite tweaking to production-ready
AgentGuard makes your AI agents robust, testable, and ready for the real world — without sacrificing speed or flexibility.
0 silent regressions — full iteration tracking
0 hallucinations — enforce factual responses
0 broken guardrails — runtime policies applied
0 missed context — structured memory, no “RAG holes”
"After months of tweaking and failing to go live, I finally got an agent in prod — with confidence — in under a week using AgentGuard."
How it works
A programmable control layer around your agents.
Bring your own LLM
Install our Python or TypeScript SDK
Use the LLM of your choice OpenAI, Claude, Gemini, Mistral…
Define your prompts and tools
We don’t replace your logic — we supervise it.
Apply guardrails at runtime
Use YAML policies to block unsafe actions or outputs.
Embed neurosymbolic memory
Your agents can persist, structure and reuse information over time.
Track every iteration
With full lineage, action logs and testable checkpoints.
Usecases: Built for real-world agents
Tested in production by teams shipping critical, customer-facing agents
AgentGuard is already protecting agents in:
Revenue workflows
B2B agents writing CRM-aware emails, scoring leads, syncing data
Customer support
Agents that escalate when uncertain, or need fallback to a human
Legal copilots
Agents parsing CVs, extracting structured data, scheduling outreach
Healthcare assistants
Agents summarizing sensitive input without missing key facts
Legal copilots
Agents navigating knowledge bases under strict compliance guardrails
