Current pain
- LLM traces alone do not explain the full workflow.
- Budgets explode before anyone sees an alert.
- Prompts, tools, and approvals change without a clear audit trail.
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Validation — agent observabilityFinally understand why your agents fail, overspend, or drift.
An open-source-first dashboard to trace runs, replay decisions, watch costs, and turn every agent failure into an actionable post-mortem.
Open-source-firstBeta design partnersDemand validation before build
-37%cost drift caught before incidents
8 minto review a full agent run
Signal
Early access
Form wired to a free local collector: SQLite storage + JSONL audit log under /var/lib/unicornhunters/landing-leads/.
The pain is already visible.
Startups, AI studios, and product teams already running agents in production with OpenAI Agents SDK, LangGraph, Dify, n8n, or in-house scripts.
A simple MVP you can sell and test.
Free self-hosted OSS. Cloud plan later from €29/month for retention, alerts, and multi-project use.
Run tracing
Timeline of tool calls, prompts, costs, errors, and human approvals.
Budgets & alerts
Thresholds by agent, project, client, or workflow with Slack/email alerts.
Short post-mortems
Automatic summary of what broke, why, and what to test next.
Hypothesis to validate
“If the pain is real, prospects will leave their email, describe the use case, and indicate budget before the product exists.”
Decision metrics
- 20+ qualified emails in 7 days
- 5+ accepted discovery calls
- 3+ prospects with explicit budget
- At least 1 priority-access request
Join the beta
Form wired to a free local collector: SQLite storage + JSONL audit log under /var/lib/unicornhunters/landing-leads/.