Agentry is a sandbox platform for managed agents by Hartie Labs: every call starts a user-specific agent sandbox in its own isolated container — preconfigured through profiles (verticals such as AI-SEO, support, data analysis, or PDF extraction). One generic image, any number of use-cases, with a live event stream, deterministic gates, and machine-readable artifacts.
Agentry
A sandbox platform for managed agents: every call starts a user-specific agent sandbox in its own container, preconfigured through profiles. One generic image, any number of verticals — formerly »KI-SEO«, now generic.
How it works
Verticals (profiles)
A profile = config (model/tools) + workspace (persona, conventions, skills). A new vertical is just a new folder — the platform shell stays the same.
Inside the platform
The same run console serves every profile: an event timeline on the left (live over SSE), observability side panels on the right. Click any shot to zoom.
Deep dive: the ki-seo flagship
A full 5-phase run (research → fact-check → draft → user review → SEO) with its deterministic gates and machine-readable artifacts.
Architecture & safety
Two isolation layers: container per run + bubblewrap for the agent's shell; --cap-drop ALL, memory/CPU/PID limits.
Provider API keys and tenant secrets are passed only as container env (AES-GCM at rest), never written to disk.
Deterministic gates around the non-deterministic LLM: factcheck_gate, json_validate, seo_score — reproducible pass/fail.
Fork-to-build: every catalog agent can be forked copy-on-write; the in-app Architect drafts SOUL/skills, nothing ships without a click.
€-metering from real provider tokens; budget overrun rejects new runs with 402 before a sandbox even starts.
Durable Postgres event log + run state machine; a typed TypeScript SDK embeds the agents into other apps with the key kept server-side.
Frequently Asked Questions
What is Agentry?
A managed-agent platform that starts an isolated nanobot sandbox in its own container per call. Use-cases are preconfigured via profiles — one generic image serves any number of verticals. The platform was formerly called »KI-SEO«; AI-SEO is now just one of the profiles.
How is each run isolated?
Two layers: outside, an ephemeral Docker container (or k8s pod) per call with --cap-drop ALL and memory/CPU/PID limits; inside, a bubblewrap sandbox for the agent's shell. The per-user workspace persists; the container is thrown away.
What are profiles and gates?
A profile bundles model, tools, persona, and skills for a vertical. Gates are deterministic code around the non-deterministic LLM — e.g. factcheck_gate (≥2 independent sources per claim), json_validate (JSON schema), and seo_score. They produce reproducible pass/fail results before publishing.
How is the platform controlled?
Through a FastAPI control plane that launches a container per call and streams normalized agent events as SSE. A Next.js web UI shows the live stream per run; a typed TypeScript SDK (@agentry/sdk) embeds the agents into other apps — the provider key stays server-side.
What does the AI-SEO flagship do?
The AI-SEO agent produces fact-checked, AI-SEO/GEO-optimized articles in five phases (research → fact-check → draft → mandatory user review → SEO optimization) and emits machine-readable artifacts such as 05-seo-meta.json (title/meta/JSON-LD/FAQ/llms.txt).