Overmind Reviews in 2026

Audience

AI product teams and ML engineers running LLM agents in production who want a cheaper specialised model they own

About Overmind

Overmind is a model training and deployment platform for teams building AI agents. It ingests production traces through OpenTelemetry and creates datasets from trace data, file uploads, and connectors for Langfuse, LangSmith, Braintrust, and Galileo. Teams can inspect agent context and runtime behavior, prepare and score datasets, evaluate prompts and models against their own examples, and optimize agent behavior through scored changes. The platform supports LoRA and full fine-tuning of open-weight models, benchmarking with configured evaluators, and deployment through an OpenAI-compatible endpoint; trained weights can also be downloaded. Users can work in the hosted console or run the platform on their own infrastructure with Docker Compose. It is designed for AI engineering and product teams operating agents in production that want to test, improve, or specialize models using their own data.

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Pricing

Starting Price:

Free

Pricing Details:

Free plan: $0/month, with fair-use OTLP ingest, up to 10 optimization runs, 5 evaluation runs, 2 training jobs, and 2 deployment jobs per month, plus 5 projects and a $40 one-time credit. Pro: $120/month with higher limits, unlimited projects, optimization runs, evaluation runs, training jobs, and deployment jobs. Enterprise pricing is custom.

Free Version:

Free Version available.

Integrations

API:

Yes, Overmind offers API access

See Integrations

Ratings/Reviews

Overall 0.0 / 5

ease 0.0 / 5

features 0.0 / 5

design 0.0 / 5

support 0.0 / 5

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Videos and Screen Captures

Overmind Dispute Resolver capability page with a system prompt and a workflow that loads a dispute ticket, fetches merchant history, calls a model, issues a refund, and returns a resolution.

Overmind Dispute Resolver capability page showing a prompt, OpenAI GPT 4.1 model, and a connected workflow for loading a dispute ticket, fetching merchant history, deciding a resolution, issuing a refund, and producing a resolution.

Overmind Training run page for a Qwen Qwen3.5 9B model, with completion status, training statistics, and loss and learning-rate charts.

Overmind Observability page listing Dispute Resolver root traces with scores, statuses, durations, tokens, costs, sources, and timestamps.

Close-up of a workflow canvas centered on a Decide resolution model-call node with five judge metrics and connected refund workflow nodes.

Train model dialog for the Dispute Resolver capability, with training and evaluation dataset selectors, grading criteria, model choices, estimated cost, and a Start training button.

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