╱╱ AGENT OPERATIONS PLATFORM

Build, measure, and evolve self‑improving agents.

A technical workbench for agent builders. Run controlled experiments, track evaluations, ship iterations, and compound learnings — all inside one operating surface.

UPTIME
99.97%
RUNS / DAY
14.2K
AGENTS LIVE
312
EVALS
8.1K

╱ 01 — PROCESS

A disciplined loop.
Build. Measure. Improve.

The platform treats every agent as a measurable system — with versioning, telemetry, and controlled experimentation on rails.

01SPEC · PROMPT · SCAFFOLD

Construct

Define the task, constraints, and evaluation criteria. Build from scratch, scaffold with AI, or upload an existing agent.

02RUNS · METRICS · TELEMETRY

Measure

Every iteration is versioned. Runs, metrics, and diagnostics are captured automatically. No hidden behavior.

03EVALS · EXPERIMENTS · DEPLOY

Improve

Run controlled experiments. Promote winners, roll back regressions, and compound learnings across your fleet.

╱ 02 — SYSTEM

Every instrument you need, on one console.

EXP

Controlled experiments

A/B prompt strategies, model configs, and agent behaviors with statistical rigor and reproducible runs.

EVL

Evaluation scorecards

Score every version across custom criteria. Track accuracy, reliability, and quality as first‑class signals.

VER

Version control

Every iteration is versioned. Promote winners. Roll back regressions. Keep a clear lineage.

TEL

Telemetry & observability

Ingest runtime telemetry from deployed agents. Detect anomalies, latency spikes, and failure patterns.

XFR

Cross‑agent learning

Insights from one experiment inform others. Reusable learnings compound across your fleet.

COM

Community discovery

Browse, fork, and build on agents shared by others. Reputation and trust scores surface what works.

╱ 03 — OPERATORS

Built for operators who ship.

SOLO

Solo builders

Ship agents faster. Let the platform handle evaluation, experimentation, and improvement so you stay focused on behavior.

TEAM

AI teams

Collaborate with governance, approvals, and role-based permissions. Keep iterations visible and coordinated.

RSCH

Researchers

Run structured experiments with real controls. Compare strategies, track metrics, publish findings.

PLTF

Platform engineers

Deploy with observability, telemetry, and automated quality gates as first-class concerns.

╱ 04 — FAQ

Questions, briefly.

01What kinds of agents can I build?+

Any. Summarization, classification, extraction, prediction, code gen, conversational. If it's an AI task, it can be built, tested, and improved here.

02How does self‑improvement work?+

Agents run controlled experiments — testing variations of prompts, parameters, and strategies against evaluation criteria you define. Winners are promoted; regressions are caught automatically.

03Which models are supported?+

Beespoke runs on OpenAI. You can choose between GPT-5.4 and GPT-5.4 mini per agent. Evaluation and improvement are consistent across both.

04How does collaboration work?+

Invite collaborators with granular permissions (view, run, edit, admin). Organizations get governance, approval workflows, and audit logging.

05Is my data safe?+

Yes. Row‑level security by default. Agents and experiments are private unless shared explicitly. Export and visibility controls remain with you.

06What does discovery look like?+

Browse community agents filtered by readiness, stability, and reputation. Fork, remix, and contribute learnings back.

╱ GET STARTED

Start building agents that measurably improve over time.

Free to begin. No credit card. First agent in minutes.