AgentMesh.help
Freemium
Developers integrating AI agents into task workflows
Paying for five separate SaaS subscriptions — a lead-gen tool, an automation platform, a coding copilot, a contract reviewer, and an AI chat assistant — while watching none of them share context is the problem adris.tech was built to eliminate.
adris is a desktop app for Windows and Linux that bundles eight modules — AI agents, automation, a code editor, local model hosting, a credential vault, DNS-level threat blocking, cross-machine RAM pooling, and a shared knowledge graph — under one login. The agents (called Krew) research prospects and verify contacts in a live browser, then hand results directly to automations that push to Slack, Sheets, or Notion on schedule. Everything stores locally in SQLite; credentials never leave the device. The ceiling appears when you need a public API to connect adris to an existing internal system — the vendor does not list one. Teams that need to pipe agent output into a custom backend will hit that wall fast.
Bottom line: Pick adris if you are a founder or small agency that wants lead research, contract scanning, and 24/7 automations on one local-first platform without stitching five tools together — but if your stack requires a public API to pull data out of the platform programmatically, adris has no answer for that today.
All 8 modules · 50 AI tasks to try · run local models · Mesh 3 devices
~4,000 AI tasks/mo · cloud automations · security scans
~16,000 AI tasks/mo · 5,000 automation runs · full Guard
Shared workspace · admin controls · SSO · priority support with SLA
View full pricing on adris.tech →
Pricing may have changed since last verified. Check the official site for current plans.
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Freemium
Developers integrating AI agents into task workflows
Free · Open source
Users seeking fully local AI agents
adris.tech is a desktop application that runs eight business AI products as a single ecosystem: Krew AI agents for prospect research and outreach drafting, an automation layer that delivers to Slack, Sheets, and Notion, a code editor with a real terminal and support for nine model providers plus Ollama, a model playground with 51 open models, a DNS-level network guard, a contract scanner (Guard), a cross-machine RAM pooler (Mesh), and a shared knowledge graph (Brain). The modules share one credential store and one knowledge graph, so a lead an agent finds and verifies flows into the same Brain that your automations and chat assistant query — no manual export or re-import required.
The defining architectural decision is local-first storage. Chat history, automation state, lead lists, and the knowledge graph live in SQLite files on the user’s machine. Credentials for Gmail, Notion, and Slack are encrypted on-device. AI calls route directly from the machine to whichever provider key the user supplies — Gemini, OpenAI, or Claude — meaning the vendor never sees the payload. For teams handling client contracts or sensitive prospect data, this is the architectural guarantee most cloud-based alternatives cannot match without a custom enterprise agreement.
The platform fits agencies and consultancies that need to scale output without headcount, founders running operations before a first hire, and engineering teams that want local model inference with Mesh pooling RAM across machines for models too large for a single device. Where it breaks: there is no public API listed by the vendor, so teams that need to pipe agent output into a custom internal system or trigger adris automations from an external event source are working without a documented integration path. At that point, teams with complex backend requirements typically move to a platform with a native API layer rather than building workarounds.
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