ReinforceNow provides an end‑to‑end platform that automates the reinforcement learning loop for LLM‑based agents, offering LoRA‑based fine‑tuning, experiment orchestration, and real‑time telemetry through a lightweight CLI. Users can upload JSONL data, run cost‑optimized training on a wide catalog of open‑source models, and export fully owned weights for deployment on any cloud or on‑premise environment.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents often require continual fine‑tuning on live production data to stay effective, but existing pipelines are fragmented, expensive, and lack built‑in observability, making it hard for teams to iterate quickly and retain ownership of model weights.
Solution
ReinforceNow offers an end‑to‑end platform that automates the reinforcement learning loop for LLM‑based agents. Users upload their data in JSONL, configure LoRA fine‑tuning, and run training via a CLI that handles experiment orchestration, versioning, and telemetry. The platform maximizes throughput and minimizes compute cost through optimized LoRA pipelines and supports a wide range of open‑source models. Real‑time telemetry provides reward metrics, trace logs, and performance dashboards to evaluate and iterate on agent behavior. After training, models can be downloaded and deployed on any cloud or on‑premise environment, preserving full ownership of the weights.
Target Audience
Primary customers are AI product teams and developers building LLM‑based agents who need continuous training on production traffic while controlling compute costs and retaining model ownership.
Features
- LoRA‑based fine‑tuning engine delivering the fastest token‑per‑second throughput for supported models (e.g., Qwen3‑8B, Llama 3.1‑8B)
- Transparent per‑token compute pricing (e.g., $0.18–$2.81 per 1M tokens) with self‑serve sandbox for instant access
- Advanced telemetry showing mean reward, run statistics, and trace IDs for multi‑turn agent evaluation
- Full experiment orchestration and agent versioning via a lightweight CLI
- Wide model catalog including Qwen, Llama, DeepSeek, and GPT‑OSS families, with custom model support for enterprise
- One‑click model export for deployment on any cloud provider or on‑premise infrastructure, ensuring weight ownership