AI agent builder without the engineering month.
Configure agent teams from a guided UI. Pick the role, connect the tools, set the goals, ship to production. No prompt engineering, no graph code, no inference infrastructure to run.
LangChain and AutoGPT are where the work starts.
Open-source agent frameworks give you primitives. They do not give you a deployed, monitored, integrated agent your team can use on Monday.
Frameworks
You write the graph, run the inference, manage memory, integrate tools, evaluate outputs, host the runtime, monitor it, and patch failures.
AstraGenie
You configure goals, tools, and guardrails. The platform handles orchestration, retries, memory, evaluation, deployment, and observability.
Result
Days from kickoff to production, not months. No ML hires, no agent infrastructure team, no on-call rotation for prompt regressions.
The five knobs that matter.
Role and goal
Pick from pre-built agents or define a new role with the outcome you want owned.
Tool access
Connect the systems the agent should read and write. OAuth or service account.
Brand and policy
Tone, restricted topics, escalation rules. Loaded once, applied everywhere.
Approval thresholds
Decide which actions ship autonomously and which need a human sign-off.
Schedule and triggers
Run continuously, on a schedule, or in response to webhooks and events.
Observability
Per-step traces, output samples, and failure summaries — built in, not bolted on.
Technical founders and ops leaders.
Engineers use AstraGenie to skip the agent-infrastructure stack. Operators use it to ship agents without engineering capacity. Either way, the time to production is days. The builder is one layer of the AI agent platform — pair it with AI agent orchestration to run multi-agent systems at scale, or deploy a pre-built AI agent team instead of building from scratch.
Configure your first agent this week.
Tell us the role you want filled. We'll have it scoped, configured, and live before Friday.