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Enterprise Layer Intelligence
Categories/AI Orchestration & MLOps/Brainbase Labs
Brainbase Labs

Brainbase Labs

Founded 2024

Host, evaluate, scale, and automatically improve autonomous agents

Pricing model

Paid

Rating

★ Mixed Reviews

Time to value

Requires Expertise

You can use Brainbase to build, deploy, and run automated AI agents across models and frameworks. It provides a standardized API and versioned registry for managing agents, skills, and tools. You can test your setups against golden datasets, track runs, inspect traces, and set up benchmarks to auto-improve performance over time. Brainbase runs isolated sandboxes on demand, balances costs, and publishes agents across multiple surfaces like Slack, Microsoft Teams, Zoom, iMessage, and native APIs without requiring custom glue code.

What Brainbase Labs does

Deploy autonomous agents with a single CLI commandEvaluate agent runs against custom evaluation rubricsOrchestrate tasks and hand-offs between multiple specialized agentsInspect trace waterfalls, token costs, and response latencySpin up elastic sandboxes across different operating systemsPublish reusable skills and tools to a centralized registryConnect agents directly to external triggers like webhooks and chat appsUniversal API to create, run, and stream agents across any modelAutomated agent improvement using golden datasets and budget constraintsVersioned package registry for agents, skills, and toolsRapid sandbox provisioning across Linux, Windows, and macOSMulti-channel deployment to Slack, Teams, WhatsApp, Zoom, and web chatEnd-to-end tracing with full waterfall logs and latency metricsQuality gates to block releases when latency, cost, or accuracy driftsNative multi-agent orchestration with state hand-offs and shared memory

Pricing breakdown

Pricing model: Paid

PlanList price
Teams$500 / mo

Tutorials & Demos

Frequently asked

SlackSlackLinearLinearGithubGithubMicrosoft TeamsMicrosoft TeamsZoomZoomModalModalDaytonaDaytonaE2BE2BNetSuiteNetSuiteWhatsAppWhatsApp

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Brainbase, AI agents, agent orchestration, LLM evaluations, managed agents API, sandboxes, prompt evaluation, multi-agent systems, trace inspection, agent deployment, automated improvement, observability