LoopLLM closes the feedback loop between production signals and model improvement. Detect drift. Correct automatically. Ship AI that compounds — not decays.
Model drift goes undetected for weeks
Users notice before your team does. Trust erodes silently.
Retraining takes weeks and $50K+ compute
By the time you retrain, production has already shifted.
Production feedback goes straight to /dev/null
Millions of signals. Zero learning. The model is frozen in time.
RLHF is a research project, not a pipeline
Manual labeling. Batch processes. No connection to live traffic.
Drift detected in real-time, auto-corrected
Quality scores tracked per output. Alerts before users notice.
Continuous fine-tuning without full retrains
Targeted corrections deploy in hours, not weeks. At a fraction of the cost.
Every production signal feeds the improvement loop
User reactions, quality scores, downstream outcomes — all captured automatically.
RLHF runs as a live pipeline, not a science fair
Automated reward signals from production. Continuous alignment. Always on.
LoopLLM tracks per-output quality scores against your baselines. When drift crosses your threshold, correction kicks in automatically — before your users file tickets.
LoopLLM turns production feedback into automated reward signals. Thumbs up, regenerations, edits, task completion — all flow into a continuous RLHF pipeline. No manual labeling.
LoopLLM applies targeted corrections to specific failure modes without full retrains. Surgical updates. Deployed continuously. Regression-tested before they ship.
A continuous improvement cycle that compounds with every production interaction.
Every model output generates structured signals — quality scores, user reactions, downstream outcomes. No instrumentation needed. Drop in and go.
Automated scoring identifies drift patterns and failure modes in real-time. See exactly where your model falls short — and why.
Targeted self-correction refines the model without full retraining. Improvements deploy continuously — then the loop begins again.
Integration time. One SDK call.
Full retrains needed post-deploy.
Continuous model improvement loop.
Founding members get locked-in pricing that never increases, direct Slack access to the team, and first priority on every new feature.
After 50 spots fill, the price goes to $149/mo. No exceptions.
Secure checkout via Stripe. Cancel anytime. No questions asked.
Not ready yet? Join the waitlist — but spots are filling.