Datastreams
    Coding agents for governed data operations

    Coding agents can work with your live business.
    Only your rules can change it.

    Connect Codex, Claude Code, Gemini CLI, GitHub Copilot CLI, Mistral Vibe or your own approved coding agent to current business context. The agent can use scoped MCP tools or invoke the Datastreams CLI; the runtime decides what may be read, changed or sent.

    The agent can write and run code. The runtime still controls the data operation.

    Approved coding clients
    Client independent

    OpenAI Codex

    Terminal coding agent

    Claude Code

    CLI and MCP client

    Gemini CLI

    Enterprise and API CLI

    GitHub Copilot CLI

    Terminal-native coding

    Mistral Vibe

    CLI coding agent

    Your own agent

    MCP, API or CLI

    Datastreams runtime

    One DimML-defined capability boundary

    Current contextPermitted actionsExecution evidence
    Business benefitUse the coding client your team already prefersOne approved Datastreams capability can work across coding agents while permissions, execution and evidence remain governed by the runtime.Examples are coding clients with documented terminal workflows. Each client can use approved MCP tools or invoke the Datastreams CLI where its capabilities and your policies permit it. Logos do not imply endorsement or a preconfigured marketplace integration.

    Why it matters and who it serves

    Give every team the speed of AI without giving up operational control.

    AI becomes useful when it can work with the business state that applies now and help move a process forward. Datastreams makes that possible through one reusable contract for context, permission, action and evidence.

    Business and operations

    Ask what is happening now and prepare the next permitted action without waiting for a new dashboard, export or manual handover.

    Faster decisions and less coordination work

    Data, IT and product teams

    Serve Codex, Claude Code, Gemini CLI, GitHub Copilot CLI, Mistral Vibe, applications and your own agents from one governed capability instead of maintaining a separate integration for every interface.

    One contract and fewer point integrations

    Risk, privacy and compliance

    Keep identity, purpose, personal context, approvals and evidence in the runtime, where they can be enforced independently of a model or prompt.

    Control and audit evidence by design

    From conversation to controlled operation

    Ask for the outcome. Keep the authority in your business.

    Natural language makes the operation accessible. It does not replace the exact contract underneath. Every client reaches the same governed source, context, rules, actions and evidence.

    1. 01

      Ask in business language

      A person or agent asks for an answer or outcome without needing to know the underlying source, schema or endpoint.

    2. 02

      Resolve current context

      The runtime selects the permitted live state, source freshness, identity, purpose and business situation needed for that request.

    3. 03

      Invoke a named operation

      The AI calls a typed query or command exposed from the approved service contract. It does not receive unrestricted database access.

    4. 04

      Validate, approve and evidence

      DimML rules validate the request, enforce authority and approvals, execute the permitted action and retain its confirmed result.

    One request, one traceable result

    The model proposes meaning. The runtime executes the agreement.

    A query returns only the permitted current view. A change must use a named, typed command. The model can vary while the operational checks remain explicit, versioned and inspectable.

    Natural-language request

    “Show the orders whose current delivery context needs service attention, then prepare the response allowed for each customer.”

    DimML-defined operation

    Resolve identity and role
    Read current order context
    Apply service eligibility rules
    Require approval where configured
    Send the permitted command
    Retain acknowledgement and outcome

    Changed data, context or rule versions may produce a different next result. Deterministic execution means the same accepted input, context snapshot and approved rule version follow the same rule-based path.

    One interface, many business contexts

    Move from asking about the business to operating it responsibly.

    The same pattern applies wherever a current answer and a controlled next action belong together. Each implementation defines its own sources, roles, freshness, actions and approval thresholds.

    Commerce

    Ask which orders need attention, explain the current delivery context and invoke the permitted service response.

    Finance

    Explain a ledger exception, prepare a correction and deliver it to Exact, AFAS or another authorised endpoint after the required checks.

    News and media

    Query current audience context and publish an allowed segment or propensity signal to the next business service.

    Connected services

    Inspect a case, handover or operational state and perform only the action allowed for that actor and moment.

    Use the interface that fits

    MCP, CLI and APIs operate the same controlled service.

    There is no separate AI copy of the business rules. People, scripts, applications and agents use the same definitions, permissions, validations and runtime evidence.

    MCP for AI clients

    Expose scoped tools to an MCP-capable client. Read-only and mutating operations remain distinguishable, and each call reaches the runtime under an authenticated authority boundary.

    Datastreams CLI

    Approved coding agents and technical teams can query current records, send governed business messages, validate definitions and inspect the same service lifecycle from a terminal. The runtime still validates every data operation against your rules.

    APIs for applications

    Portals, apps, services and agent workflows use the same permitted queries and actions without rebuilding the processing agreement in every interface.

    Bring one AI question and the business action that should follow.

    Start with one live question and one governed action. We map the context, command, deterministic checks, approval and result into one controlled service.