Seed Stage · Confidential · 2026
The agents keep running. The problems keep growing.

You deployed AI agents.
The quality layer is missing.

AgentIQ is the quality layer that existing observability tools don't have — loss patterns that surface as they form, quality scores calibrated to your industry, and a feedback loop so agents improve continuously without a code push.

01
How AgentIQ Works
1
Connect
One line of code. Any framework — LangChain, CrewAI, or fully custom. No rebuilding. No downtime.

If AgentIQ goes down, your agent keeps running. It's invisible to your users.
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2
Score
Every interaction evaluated — nothing sampled. Quality defined by your industry and refined by your team.

Healthcare agents scored on accuracy and safety. Retail agents on task resolution. Coding agents on correctness. Marketing on brand alignment.
→
3
Surface
Loss patterns appear in the dashboard as they form. Root cause in plain English. Not "error rate is 23%" — but exactly which step is failing, why, and since when.
Quality score per interaction
0–100, calibrated to your industry. Scored on four dimensions: accuracy, goal alignment, decision quality, completeness.
"This interaction scored 34 / 100. Goal alignment failed — agent redirected to wrong flow at step 2."
Loss patterns with root cause
Automatically grouped by failure type, workflow step, or tool. Root cause in one sentence. No manual log review.
"Billing disputes failing 47% of the time because payment API times out at step 3. Happening since last Tuesday."
Feedback loop
Every confirmed failure feeds the improvement cycle. Agents get measurably better. Same failures stop repeating.
"After fixing step 3 timeout: billing dispute pass rate went from 53% → 91% in 48 hours."
02
Why Existing Tools Miss This
Tool
What they do
100% Coverage
Loss Patterns + Feedback Loop
LangSmith
LangChain · $125M raised
Traces and debugs agent workflows. Samples traffic. No loss patterns or feedback loop.
Samples
None
Braintrust
AI observability + evals. Samples production. No industry defaults. No feedback loop.
Samples
None
Maxim AI
Simulation + evals + observability. Complex enterprise sales. Samples production.
Samples
Partial
Microsoft Foundry
Launched Build 2026
Cross-framework tracing. OpenTelemetry-based. No loss patterns. No feedback loop.
Partial
None
Galileo
Acquired · Cisco 2026
GenAI evaluation and hallucination detection. Acquired April 2026. Gap is open.
Acquired
Gap open
AgentIQ ✦
Seed · 2026
The quality layer. Loss patterns surface automatically. Every failure feeds the improvement loop. Industry defaults out of the box. Deploys inside your VPC.
100%
Core
03
Data Never Leaves Your Infrastructure

Agent interaction logs contain customer conversations, PII, and proprietary business workflows. AgentIQ deploys inside your own servers — the same infrastructure your agents already run on. One command. No external data transfer. No shared endpoints.

⭐ Recommended for Enterprise
Self-Hosted via Docker
Your team installs AgentIQ inside your existing servers or cloud account. All data stays inside your network. We provide the installation package — you own the infrastructure.
Setup: 3 steps, ~10 minutes
Cloud Deploy
AWS / Azure / GCP VPC
Deploy AgentIQ inside your cloud VPC. Your database, your network, your security perimeter. Data never leaves your cloud account.
Demo Only
Render (Shared Cloud)
AgentIQ's public demo environment. Good for evaluating the product. Not for production data or enterprise deployment.

This document is for external audiences — investors, design partners, developers evaluating AgentIQ. It deliberately omits model names, table schemas, queue mechanics, retry logic, and implementation details.