[gtranslate]
Start a Free Trial

Engineering Intelligence Platform

  • AI Engineering & Requirements Management Software

Give AI Agents
Governed Access to
Your Requirements Data

Fast-moving engineering teams use AI Engineering orchestration to connect Claude, ChatGPT, Copilot, or any AI agent directly to requirements, traceability, risk, and compliance data, governed inside Visure, not around it.

Start a Free Trial
Watch a Demo
  • Most cost-effective
  • Access All Features
  • 14-Day Trial
Visure MCP

The Challenge

Most AI Tools Operate Without Product Context

Coding assistants and generative AI have sped up content production. They haven’t solved
requirements quality, traceability gaps, or compliance complexity, because most
AI has no access to requirements, tests, risks, or verification evidence in the first place.

AI Hallucinations

Without grounded product data, AI fills gaps with plausible-sounding but incorrect answers.

Fragmented Workflows

Engineering data scattered across disconnected tools with no single governed source of truth.

No Auditability

AI-generated changes with no version history and no approval trail for regulators to inspect.

Inconsistent Decisions

The same question asked twice returns two different answers, with no shared context to reconcile them.

Late Compliance Risk

Compliance gets discovered during the audit, not caught while requirements were being written.

Costly Rework

Requirement gaps discovered late in development cost far more to fix than they would upstream.

Two Ways In

AI Inside Visure, and AI From Anywhere

Visure is an AI-powered Requirements Management platform. Its Engineering Intelligence module gives you two ways to bring AI into your engineering process, both governed by the same underlying data model.

In-App Assistant

Vivia

Contextual, RAG-based AI that works from within a document or project, grounded in your knowledge base: normative references, project documents, internal policy.

External Access

MCP Server

A dedicated API connecting external AI agents, Claude, ChatGPT, Copilot, or your own model, directly to Visure to create, trace, and analyze inside your governed process.

The Core Idea

From Integration to Orchestration

Engineering data has traditionally moved between tools one link at a time: a proxy element here, a reference there. The VISURE MCP Server enables something different: AI orchestration across your entire engineering toolchain.

  • Tools stay where they are. Requirements, MBSE models, test results, and source code remain in their own systems.
  • Data flows in real time. AI agents pull the right data to the right user in the right interface, without manual re-entry.
  • Governance travels with it. Every hop stays inside Visure's governed data model, never around it.
Visure MCP Orchestrator

How It Works

Every AI Response Is Grounded Before It Reaches an LLM

Data is retrieved, contextualized, and reasoned over inside a governed pipeline, so the answer that comes back stays traceable to its source.

Data Sources

Requirements, tests, risks, docs, traceability

Ingest & Embed

Structured, role-aware indexing

Knowledge Graph

Graph RAG pulls relevant context

AI Reasoning

Your chosen LLM, grounded in context

Secure Response

Traceable to source, fully audited

Workflows

AI Engineering Workflows, Organized by Category

Eight categories of AI Engineering work, each running inside Visure’s governed data model. Select a category to see it in action.

01 · AI Requirements Authoring & Decomposition

Stop retyping the same information into five different documents.

Generate requirements, test cases, risks, and RFP responses directly from existing content, with AI validating intent rather than just producing text, and full traceability created as it goes.
  • Requirements Decomposition, Concept to Subsystem. Describe a feature in natural language; the AI agent decomposes it into a full requirements hierarchy, stakeholder to subsystem, with traceability at every level.

Authoring Velocity

4 x

Faster requirement drafting

02 · Requirements Quality & Review

Stop discovering requirement gaps during the audit, not before it.

AI reviews requirements against your own quality bar, completeness, testability, ambiguity, and standards compliance, and documents every revision with the rationale behind it.
  • Requirement Quality Review with AI Analysis. An agent reviews requirements for completeness, testability, ambiguity, and standards compliance, adding comments with fixes.

Quality Coverage

98 %

Requirements reviewed for ambiguity

03 · Traceability & Impact Analysis

Stop losing time rebuilding trace matrices by hand.

AI agents maintain bidirectional traceability across requirements, risks, tests, and code, and surface downstream impact the moment something changes, not weeks later.
  • Impact Visibility Before Commit. Engineers view related tests, risks, and downstream requirements to understand system impact before code is committed.

Traceability Coverage — Program View

97 %

Requirements traced to test evidence

04 · Test Case Generation & Verification

Stop writing test cases from scratch for every requirement.

Pull system requirements straight from Visure, generate verification test cases for each, and link them back automatically, so test coverage and traceability stay in sync.
  • Test Case Authoring with Verification Traceability. Pull system requirements from Visure, generate test cases for each, and link them back via the chosen relationship type.

Verification Throughput

3 x

Faster test case authoring

05 · Toolchain Orchestration

Stop manually re-entering the same change across five different tools.

AI agents connect to your MBSE tools, test platforms, and issue trackers, so data flows to the right place automatically, without leaving a traceability gap behind.
  • Sprint Planning from Requirements. The agent reads approved requirements, estimates effort, and creates sprint work items in Jira or ADO, linked back to source IDs.

Connected Toolchain

5

Tools synced in real time

06 · Code & Development Integration

Stop losing traceability the moment code gets written.

Engineers create trace links between code changes and requirements the moment implementation happens, from inside the IDE, so traceability stays synchronized with development activity instead of reconstructed later.
  • Code-to-Requirement Linking. Engineers create trace links between code and requirements the moment implementation happens, from inside the IDE.

Development Activity

0

Traceability gaps at commit time

07 · Change Management & Impact Propagation

Stop finding out about a downstream break after it ships.

Every AI action operates within Visure’s data model, which defines what artifacts exist, what process they follow, and what approvals are required, with a human in the loop at every critical decision.
  • Change Request with Automated Impact Propagation. An engineer flags a change; the agent traces every impacted item and opens a change request within Visure's approval workflow.

Change Impact

100 %

Impacted items traced automatically

08 · Compliance & Audit Readiness

Stop scrambling to assemble audit evidence at the last minute.

After a design review, the agent updates requirements from feedback, documents the rationale, and creates a new baseline, so every revision stays audit-ready with a documented history, not reconstructed under deadline pressure.
  • Cross-Iteration Requirement Refinement. After a design review, the agent updates requirement descriptions based on feedback, documents the rationale, and creates a new baseline.

Audit Readiness

100 %

Baselines created automatically

INTEGRATIONS

Works With Your Existing Toolchain

The MCP Server orchestrates AI across the tools your teams already use, no rip-and-replace required.
Explore Integrations
Jira
IBM DOORS
GitLab
Azure DevOps
Simulink
VectorCAST
MS Word/Excel
Fusion Manage
Ent. Architect
Confluence
MATLAB
ReqIF
Micro Focus
Rapita Systems
TASKING
PTC Windchill

Compliance & Governance

Built for Regulated Industries

Engineering Intelligence is designed for environments where compliance and traceability cannot be compromised, every AI action is governed by the same rules your engineering process already follows.
Aerospace & Defense
  • ARP 4754A
  • DO-178C
  • DO-254
Learn more
Automotive
  • ISO 26262
  • ASPICE
  • SOTIF
Learn more
Railways
  • EN 50128
  • IEC 61508
  • EN 50129
Learn more
Medical Devices & Life Sciences
  • IEC 62304
  • ISO 14971
  • EU MDR
Learn more
Energy Systems
  • IEC 62443
  • IEC 61508
  • NERC CIP
Learn more
Oil & Gas
  • API 1164
  • IEC 61511
  • ISO 20815

Deployment

Your Data Stays Yours

Visure Server, database, and the AI layer can run entirely on-premise. The only external connection is to the LLM of your choice, and that traffic never passes through Visure.

Your Environment

On-premise or your private cloud
  • Visure Server
  • Database Server
  • AI Layer — Vivia & MCP Server

ENCRYPTED CONNECTION

Only this link leaves your environment

LLM Provider

Your choice, your agreement
  • Logo ClaudeLogo vectorial coral sobre fondo blanco. Claude
  • Logo OpenAILogo vectorial negro sobre fondo blanco. ChatGPT
  • Azure AI Foundry
  • Ollama / Self-hosted

Only one connection ever leaves your environment: the link to your chosen LLM.

Why Visure

Key Benefits

Trusted AI
Outcomes

AI-generated requirements and analyses created within governed processes.

End-to-End Traceability

AI-assisted traceability across requirements, risks, tests, and compliance evidence.

Reduced
Rework

Catch requirement gaps and downstream impacts earlier in the process.

Compliance by Design

Compliance built into the workflow, not bolted on as a late-stage activity.

Governance & Auditability

Full approvals, permissions, and audit trails, even as AI adoption scales.

Human-in-the-Loop

Engineers stay in control of every critical decision, always.

MCP Server

Frequently Asked Questions

Can’t find an answer? Contact our team →

The VISURE MCP Server is a dedicated Model Context Protocol implementation that connects AI agents, such as Claude, ChatGPT, or Copilot, directly to Visure's requirements, traceability, risk, and compliance data. It lets any AI agent read from and act on your engineering lifecycle data inside a governed process, rather than working from copies or exports.

Custom integrations can connect an AI agent to your data, but they typically lack governance, traceability, and audit controls out of the box. The VISURE MCP Server is designed specifically for enterprise engineering workflows: every interaction respects existing roles and permissions, follows your defined lifecycle process, and is captured in version history automatically, so you're not rebuilding governance from scratch.

Explore More

Related Resources

Data Sheet

The full technical overview of the MCP Server, workflows, and deployment model.

Download PDF

Webinar Recording

High-Velocity Engineering with MCP: AI Agility, Traceability & Governance.

Watch Now

Integrations Hub

Browse all 30+ tools that connect natively with Visure and the MCP Server.

Integrations

Get Started

Ready to Put AI Inside a Governed Engineering Process?

Tell us about your engineering environment, and our team will follow up with next steps for enabling the MCP Server for your organization.

Talk to Our Team

Get a walkthrough of the MCP Server for your engineering environment.

By submitting you agree to Visure’s Privacy Policy.

  • 14-Day Trial
  • Cancel Anytime
  • All Features Included

Search

Find resources, features and more.

Watch Visure in Action

Complete the form below to access your demo

Register Now!