The enterprise integration platform

Workflows you draw.Software you own.

Draw a workflow. Get running software on infrastructure you control. What took quarters now ships in days.

How Alphanetix works: you design a workflow on a visual canvas, the platform compiles it into a native Java microservice, ships it to your own server over SFTP, health-checks it, and it runs live serving requests.

Connects with the systems you already run

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Why teams switch to Alphanetix

Own it, don’t rent it.

Workflows compile into services on your infrastructure. No per-task fees, nothing to migrate off later.

Days, not quarters.

Analysts build on a canvas, AI drafts flows against your real systems, and IT keeps control.

Built for regulated.

Data stays inside your compliance zone; every release is git-audited with clean rollback.

Built on a canvas, by your team

Every workflow is three layers deep, and none of them is code.

Connect what you already run

HTTP, databases, Kafka, Redis, AI services: each becomes a configured connection your whole team reuses.

Match the fields, visually

Draw a line between two systems and their fields line up. Fuzzy auto-match and AI mapping do most of it for you.

Encode the rules, without code

Conditions, transformations and validations, assembled from blocks that analysts and engineers read alike.

See how the platform works
studio.alphanetix.io

Not Just Automations. Software.

Most platforms interpret your diagram inside their cloud, forever. Alphanetix compiles it into a native Java microservice, shipped to a server you control.

Your cloud Your data center Your compliance zone
AI flow generation
Create an order intake flow: accept orders over HTTP, validate them, store in PostgreSQL and notify Kafka.

Done - I used your existing orders_db and events-kafka connections.

4 nodes2 mappingsvalidation logic

Generated against your real connectors - reviewed, then published by you.

AI that builds with you, under guardrails

Describe a flow in plain language and watch it appear on the canvas, wired to your actual systems. Nothing runs until a person publishes it.

  • AI agents with boundaries. Chat agents can search your knowledge and call only the workflows you allow: deny by default, governed platform-wide.

  • Your models, your rules. Run on local models via Ollama or vLLM, or bring Claude and other cloud models. Usage is governed centrally.

  • Open to outside agents. An MCP server lets Claude, Cursor or Copilot build and deploy on Alphanetix. The platform needs no AI key of its own.

Beyond the canvas

What the evaluation checklist asks about next, covered in the same platform.

An audit trail your regulator accepts

Every release is a git-backed version with a commit message; rollback is a clean, auditable roll-forward.

Fewer tools to buy

Connectors, logic, clustering and API publishing in one platform. Line items that usually mean three more vendors.

Partners integrate without seeing inside

Share a read-only OpenAPI portal for chosen endpoints, with revocable links. Internals stay internal.

Made for regulated, real-world industries

From regional banking rails to hospital systems, where data can't leave the building.

The full story · 3 minutes

See your first workflow running on your own server

A 30-minute walkthrough with an engineer: your systems, your use case, a live deploy.

Free pilot available · cloud and on-premises, with enterprise support