For every agent, at any scale
Quotient enables agents across industries to continuously learn, adapt, and improve. All using real-world feedback.
One-time 5-minute setup
Improvement never stops
Deploy Once, Improve Forever
Agents that keep betting better every day
Your agents continuously improve from real production behavior, adapting automatically as your product and users evolve. No extra datasets, prompts or effort required; the more your agents work, the better they will get.






Tailored to your product and domain
Every agent decision becomes a learning signal, producing models that grow more specialized in your workflows, rules, and domain.










Dramatically higher accuracy & reliability
Our domain-aware reward models catch mistakes generic metrics miss, making your agents far more predictable and trustworthy.



Fully automated improvement pipeline
Quotient handles telemetry, evaluators, reinforcement, and inference, offering you continuous improvement without any infrastructure to build or maintain.






























Flexible production-ready model deployment
Every model is delivered as a production-grade endpoint your team can use immediately, or self-host in your own cloud for full control.































Quotient is now an essential part of our stack
"Quotient has been a real game-changer and is now an essential part of our infrastructure stack. Having this high level of monitoring and transparency has even factored into our investor due diligence conversations. Our users trust us to have the best AI search solution, and we trust Quotient."
Rotem Weiss
—
CEO & Co-Founder of Tavily
Pricing Options
Start
FREE
Track
$249/month
on qwen and OpenAI models
($0.50 per 1,000,000 tokens)
Evolve
Starts at $1,500/month
on qwen and OpenAI models
with advanced training quotas
The trace-native learning system for AI agents
Learns directly
from agent traces
Extracts reward signals directly from OpenTelemetry agent traces. No labels, no synthetic benchmarks.
Detects failures
humans miss
Limbic automatically identifies tool-use errors, hallucinations, and retrieval failures across full multi-step agent trajectories.
Turns signals into
ranked insights
Issues are grouped, scored, and prioritized by user impact, frequency, and fix effort, so teams know exactly what to fix first.
Improves agents
automatically
Limbic converts real agent behavior into reward signals and continuously fine-tunes models. Deploy once, improve forever.













