Legacy-System AI Integration

AI-Native Business Systems

Make your existing business systems easier for approved AI assistants and other software to understand and use.

Brownsmith Dynamics documents, structures, and connects the systems you already depend on. A useful first implementation may retain your spreadsheets, CRM, email, internal portal, file store, or older application.

Discuss Your Systems Explore the Brownsmith Dynamics MCP

Document before automating

Connect selected systems in stages

Keep permissions narrow and revocable

The Problem

AI Cannot Reliably Use What the Business Has Not Defined.

Critical knowledge exists only in employees' heads.

Information is distributed across files and platforms.

APIs exist but lack usable AI-facing documentation.

Workflows depend on repeated manual transfers.

Business rules remain informal or inconsistent.

Different teams use different systems for the same process.

AI assistants lack trusted access to current company information.

Legacy applications cannot easily join new agent workflows.

What Brownsmith Dynamics Adds

A Layered Implementation Around Existing Operations.

System and Workflow Discovery

Identify the systems, people, data sources, handoffs, business rules, exceptions, and failure points involved in a real workflow.

Knowledge and Documentation Preparation

Turn terminology, policies, system behaviour, source ownership, and operating procedures into material that people and machines can follow.

API and Data-Source Mapping

Document which existing interfaces can read or change information, what authentication they require, and where a safer adapter is needed.

MCP Server Design

Expose a limited catalogue of approved information and tools through Model Context Protocol when the client environment supports it.

Tools, Skills, Plugins, or Apps

Package useful operations and instructions for the AI products and workflows selected for the project. Provider terminology and support differ.

Permissions and Approval Controls

Start with the least access required, separate read and write operations, and place human approval before consequential actions.

Testing and Evaluation

Test correct, incorrect, incomplete, adversarial, stale, and permission-limited inputs against expected business outcomes.

Deployment and Ongoing Maintenance

Document ownership, secrets, monitoring, provider changes, data refresh, evaluation, incident handling, and the path for safe expansion.

What May Be Delivered

The Output Depends on the Systems and Provider Support.

Provider capabilities and terminology change. The final scope names the supported products, access model, tools, and maintenance responsibilities rather than assuming feature parity.

System inventory and workflow maps
Machine-readable business documentation and llms.txt
API and data-source documentation
A read-only or carefully scoped MCP server
Read-only search tools and approved action tools
Provider-compatible apps, connectors, skills, or instructions where supported
Internal agent instructions and reusable prompts
Permission policies and human-approval workflows
Audit logging and integration tests
Evaluation datasets and operational documentation
A deployment, maintenance, and expansion plan

From Legacy to AI-Accessible

Increase Capability One Controlled Stage at a Time.

Stage 1

Document

Make systems, terminology, policies, data sources, owners, and workflows understandable.

Stage 2

Read

Let approved assistants search and retrieve trusted information without changing the source.

Stage 3

Assist

Allow assistants to draft outputs, compare evidence, and recommend a next action.

Stage 4

Act With Approval

Permit selected operations only after an authorised person reviews and approves them.

Stage 5

Controlled Automation

Automate only mature workflows that are observable, bounded, and reversible.

Illustrative Use Cases

Grounded Work, Not Broad Autonomy.

The following examples illustrate work that may be possible after system review and implementation. They are not a claim that every capability is currently available for every client or provider.

Find current product and service information.

Retrieve an approved internal policy or document.

Locate the correct public contact or meeting link.

Draft a customer response from approved company information.

Check inventory through an existing system.

Prepare a quotation for human review.

Summarise authorised account history.

Route an enquiry to the right team.

Update one approved CRM field after confirmation.

Produce a recurring operational report.

ChatGPT, Claude, and Gemini

Use Familiar AI Products Where Support Allows.

An implementation may let customers or employees ask about approved company information, locate links and contacts, retrieve documentation, draft communications, or invoke controlled tools through AI products they already use. Technical and contractual support differs across products, plans, workspaces, APIs, connectors, and MCP clients; identical feature parity should not be assumed.

What This Service Does Not Mean

Modernisation Without Unnecessary Replacement.

Replacing every existing system.
Training a proprietary model.
Giving AI unrestricted access.
Automating every decision.
Moving all data into one platform.
Removing human oversight.

Security and Control

Access Must Match the Task.

Least-privilege access and read-only defaults
Per-tool permissions and revocable access
Human approval for consequential actions
Identity-aware access where the client system supports it
Audit records that connect actions to users, tools, and sources
Secret management without exposing credentials to prompts
Input and output validation
Rate limits and abuse controls
Defined retention and deletion practices
Provider-specific privacy and contract review

Engagement Process

Start With One Reviewable Workflow.

01
Initial System Review
Understand the operating environment, current systems, objectives, and constraints.
02
Opportunity and Risk Mapping
Compare potential value with data, permission, reliability, and change-management risks.
03
Pilot Selection
Choose one bounded workflow with useful evidence, a clear owner, and measurable success criteria.
04
Documentation and Integration
Prepare sources, interfaces, instructions, permissions, and the selected AI-facing layer.
05
Evaluation
Test usefulness, accuracy, security boundaries, failure cases, and human review effort.
06
Controlled Deployment
Release to a defined group with observable limits, support, and rollback options.
07
Maintenance and Expansion
Refresh knowledge, monitor provider changes, review usage, and add new capability only when the evidence supports it.

Request an AI Readiness Review.

Bring the systems, repeated transfers, undocumented rules, and AI use cases your team is considering. The first conversation can identify a proportionate pilot and the controls it needs.