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Connectors

Reach your systems without writing the glue.

A connector is a node. Drop it into a workflow, call it like any other step, under the same guardrails and the same audit trail.

What ships prebuilt

The systems the work already lives in.

Each family is a set of documented nodes in the agent editor, not a sample script — and the same node in every deployment.

  • Databases and warehouses

    Query the systems your records live in as a step inside a workflow, with the result available to the next node — instead of exporting data to somewhere the model can reach it.

  • Search, knowledge and governance systems

    The enterprise search and knowledge platforms your organisation has already standardised on, used as a retrieval source under the same grounding checks as any other.

  • Cloud storage and content management

    Read from and write to the object stores and document libraries where policies, contracts and procedures are kept, including writing a generated document back.

  • Development and collaboration tooling

    Issue trackers, code hosting, boards and team messaging — where work is requested, and where the answer has to land for anyone to see it.

  • Workplace productivity suites

    Mail, calendars, documents and files, so an agent can prepare and file work in the tools people already have open.

  • Email and file transfer

    Mail over your own SMTP server and scheduled file drops over SFTP — the transport layer a regulated organisation still runs on.

  • Web search and retrieval

    Fetch and search public sources as an explicit, governed step — screened on the way in like any other untrusted content, never an implicit fallback when the corpus comes up empty.

  • Audit destinations

    The audit stream exports to object storage, to Splunk, to Datadog, or to your own collector — so the record lives in your security telemetry, not in a vendor console.

The node library

One card per system, maintained with the platform.

Each card is a node in the agent editor's function library: drop it on the canvas, fill in the query and the connection, and the result is a variable the next node can read.

MySQLConnects to a MySQL database, runs the SQL query you give it and returns the rows — as plain sentences or as CSV — for the next node to use.

When nothing prebuilt fits

A connector catalogue is finite and your estate is not. These are why a missing connector is an afternoon rather than a roadmap request.

  • The REST node

    Anything with an HTTP API is reachable as a step: URL, headers, body and operation set on the node, credentials pulled from the secrets you keep on the Configure tab.

  • Agents over MCP

    Your agents are exposed as MCP tools, so an MCP client your team already runs can call a governed agent as a step — same guardrails, same run record.

  • Models as cards

    A model is configured the way a connector is: a card, with the functions it serves ticked. Swap one and nothing built on top moves.

Start from something

Ready-made agents, editable from the first minute.

Templates you open, point at your data and change. Every node is visible, and the moment you edit one it is your agent.

  • Marketplace card: Custom RAG Director
  • Marketplace card: Query Disambiguator
  • Marketplace card: Confidence Enforcer
  • Marketplace card: Prompt Injection Guard
  • Marketplace card: Corporate Logging Agent
  • Marketplace card: Create Red Team Plan
  • Marketplace card: Conditional Flow Builder
  • Marketplace card: LLM Plan & Act
  • Marketplace card: Contract Analyst
  • Marketplace card: Output Feedback Validator

Slide 1 of 10

Three questions about connecting it to anything.

Connecting an AI system to your systems of record is where a security team stops nodding, so it is worth being precise.

  1. Does connecting a system mean our data leaves it?

    No. A connector runs where NeuralSeek runs — for a regulated deployment, inside your boundary, over your network. The only call that can leave is the model call, and a model you host closes that too.

  2. Where do the credentials live?

    On the Configure tab, as named secrets. A workflow references a secret by name and never shows its value — it is inserted from a menu in the editor, not pasted into the agent.

  3. Can an agent write to a system, not just read from it?

    Yes, through the same nodes that read. What a step sent and what came back is in the run record, and a saved agent only runs when something calls it — an API request, or a schedule you set.

See it running inside your own boundary.

Talk to a NeuralSeek expert about how it fits your stack, where your data has to live, and the governance your auditors already expect.