Skip to main content
M&S Consulting

ARTIFICIAL INTELLIGENCE CONSULTING

Connect AI to the work your enterprise runs on.

Discuss your AI project
24+
Years integrating AI & analytics
Machine learning and agentic AI
End to end
Enterprise AI integration
CRM, ERP, cloud, and data systems
250+
Consultants on staff
Commercial and federal experience

Complex enterprise workflows need more than a model. We connect AI to your applications, data, and teams, with governance and security that give commercial and federal clients the confidence to operate at scale.

Tell us what you want AI to do.

Discuss your AI project

WHAT WE DO

From enterprise architecture to working AI

Strategy, integration, governance, and ongoing delivery belong in the same program.

AI strategy & roadmap

We help you decide where AI is worth using, which use cases can return value, and how to phase the work around your data, infrastructure, timeline, and risk limits. The result is a practical roadmap with clear priorities.

Security & governance for AI

Governance makes wider adoption possible. We build data protection, clear permissions, evaluation, human review, and escalation into the workflow so teams can use AI confidently and keep improving it.

Agentic AI & automation

Agentic AI can plan, carry out, and adjust tasks as conditions change. We design workflows that let AI take approved actions across your CRM, ERP, marketing tools, and data systems while people retain oversight.

AI-ready data architecture

Reliable AI depends on reliable data. We design clean pipelines, governed data stores, and quality controls so teams can audit the system and improve it over time.

PLATFORM EXPERIENCE, CONNECTED

AI expertise backed by the systems your business already uses.

Our Anthropic partnership and enterprise platform experience come together in workflows spanning customer records, operations, finance, and team knowledge.

AI GOVERNANCE & DEPLOYMENT ARCHITECTURE

Governance gives your AI program room to move.

Clear permissions, evaluation, and review paths let teams put AI to work with confidence. We help commercial and federal clients build those controls into production delivery, with evidence that supports security review and continued adoption.

  • Enterprise workflow design
  • Role & permission architecture
  • Deployment pattern routing
  • Audit & evidence design

THE PROBLEM

Vendor review and deployment review answer different questions

A vendor certification may show that the provider meets a standard. It does not show whether your roles, data access, workflows, and logs are configured safely. The deployment review determines whether the system is ready for production.

Symptom one

The indefinite security review

Security teams ask architecture questions. Project teams answer with a vendor questionnaire. Months pass without a decision.

Symptom two

The over-built pilot

A team commissions a custom application for work that a configured workspace could have handled in days. The organization now has to own all six control layers.

Symptom three

The permission collapse

An integration uses one privileged service account and bypasses the institution's existing access controls.

OUR FRAMEWORK · PART ONE

Six parts of AI governance

Each part answers a different question, produces a different work product, and has a different owner. Defining them turns a broad governance review into a work plan.

01

Identity & access

Who may use it at all?

Work product

Role matrix; federated sign-in and automated deprovisioning

Owner IT / Identity

02

Data boundary

What can it see?

Work product

Scoped system connections; retention and residency policy

Owner Data governance

03

Capability permissions

What actions can it take?

Work product

Read/write matrix; approval gates on state-changing actions

Owner Business + Security

04

Behavioral constraints

What should it say and refuse?

Work product

A written policy and a test suite that shows whether it holds

Owner Use case owner

05

Observability & audit

Can we prove any of this?

Work product

Log export into existing monitoring, DLP and discovery tooling

Owner Security operations

06

Lifecycle governance

Who approves the next change?

Work product

Intake, review body and defined re-review triggers

Owner Steering committee

Policy and configuration define five layers. System behavior takes testing to show that the controls work.

Many governance documents make a claim without providing the evidence. We build a test suite that reviewers can inspect.

OUR FRAMEWORK · PART TWO

Three deployment paths. One deliberate choice.

Start with the controls you already have. Configure the platform when that is enough. Build custom software only when the use case requires a level of control the platform cannot provide.

Platform controlCustom control
01

Pattern 01

Governed platform, as issued

The enterprise product under institutional administration, used broadly for assistive work with a person in the loop.

Control model

Platform provides all six layers

Delivery

Available across approved use cases

02

Pattern 02

Most use cases start here

Configured surface inside the platform

A shaped workspace on the same governed platform: curated knowledge, scoped connections, packaged instructions and repeatable automations for one workflow.

Control model

Platform provides most controls

Delivery

Configure the remaining controls in days

03

Pattern 03

Purpose-built application

Custom software built against the model API, with its own interface, workflow logic, storage and audit trail. Some use cases require this level of control.

Control model

Your team owns all six layers

Delivery

Treat it as a funded software project

ROUTING RULE

Configure before you commission a custom build.

A purpose-built application makes your team responsible for every control the platform previously supplied. Use it when the workflow truly requires custom software, not simply because the configured option was never evaluated.

HOW WE WORK

Five phases in an order that avoids rework

Routing a use case before mapping its roles and permissions creates rework. We settle those decisions before configuration or development begins.

  1. 01

    Assess & prioritize

    Inventory candidate use cases and score them on value, risk and feasibility.

    Output

    A ranked portfolio

  2. 02

    Map roles & permissions

    Define who can act, which data they can use, and which actions need approval.

    Output

    The governing matrix

  3. 03

    Route each use case

    Assign every item to a deployment pattern, with written rationale.

    Output

    A build plan

  4. 04

    Configure, then build

    Platform-wide controls first; per-use-case work second.

    Output

    A governed environment

  5. 05

    Prove & govern

    Behavioral tests, audit pipeline, review cadence and re-review triggers.

    Output

    Defensibility

WHAT YOU GET

What we deliver

  • 01

    Prioritized portfolio of use cases

    Scored, including the use cases we recommend declining and why.

  • 02

    Role × data × capability × approval matrix

    The artifact that drives configuration, scoping and routing.

  • 03

    Deployment pattern assignment

    Every use case routed with rationale a reviewer can challenge.

  • 04

    Six-layer control architecture

    Including where the model runs and under whose compliance perimeter.

  • 05

    Behavioral test suite

    Tests that show whether the behavioral constraints hold.

  • 06

    Audit and evidence design

    Log flow into existing monitoring, DLP and discovery tooling.

  • 07

    Governance operating model

    Intake, review body, approval thresholds and re-review triggers.

  • 08

    Executive and board briefing

    The same architecture translated for the people who fund it.

WHO WE HELP

For organizations where AI has to stand up to scrutiny

Sensitive data, decentralized teams, and formal review change what responsible deployment requires. We build the controls and evidence that let these organizations move forward with confidence.

Enterprise

  • Regulated data under retention, residency or discovery obligations
  • A security function that must sign off before production
  • Existing identity, DLP and monitoring investments that AI must fit into
  • Multiple business units requesting AI faster than governance can review

Higher education

  • Student-record obligations and layered faculty, advisor and staff entitlements
  • Decentralized units adopting AI independently of central IT
  • Research data with contractual restrictions on where it may be processed
  • Governance bodies that require a defensible position before approving a pilot

START THE CONVERSATION

Bring us the workflow you need to move forward.

We connect the business outcome, systems, and access requirements into a delivery plan. Governance supports the work from design through adoption and ongoing operation.

Discuss your AI project
Collage of hands typing on a keyboard

THE M&S FIELD NOTES

Field notes for leaders working with complex technology

M&S practitioners share practical notes on AI, cloud, data, security, and enterprise systems.

Practical, specific advice
Enterprise use cases
Notes from practitioners

Join the list

Short notes for leaders making complex systems work.

No spam. No list swaps. Unsubscribe anytime.

ENTERPRISE AI DELIVERY

Build AI into the way your enterprise works.

Connect complex workflows, enterprise applications, and governed data. M&S brings systems integration and AI expertise to commercial and federal programs.

Bring us a business process, an integration challenge, or an AI program that needs to move into production.

What we help you deliver

  • Connected workflows

    Agents and integrations across CRM, ERP, and operational systems.

  • Governance that supports adoption

    Clear permissions, human decisions, and evaluation built into delivery.

  • A path into operations

    Cloud engineering, monitoring, ownership, and team enablement.

HOW WE HELP

Additional AI services

We review your current systems and candidate use cases, then rank the work by value, feasibility, risk, and timing. The roadmap shows what to do now and what to defer.

We define the policies, review points, escalation paths, and audit evidence for each AI workflow. These controls protect data and keep autonomous actions within your ethical and regulatory requirements.

We design the data warehouses, lake architecture, integration pipelines, and quality controls that supply AI systems with governed, reliable data.

We identify repetitive work that is worth automating and design workflows that keep human judgment where it is needed. The result should reduce effort without creating a harder process to manage.

We design clear interfaces, provide training in the workflow, and collect feedback from the people doing the work. Teams are more likely to use a system when they understand its results and limits.

We add AI capabilities to Salesforce, SAP, Oracle, and Microsoft 365. This can improve existing workflows without adding another standalone tool for teams to manage.

We design and manage the cloud infrastructure behind AI workloads on AWS, Azure, and OCI, and integrate those workloads with enterprise SaaS applications such as Salesforce.

When existing tools do not fit the workflow, our developers build custom models and agentic applications around your architecture, data, and budget.

Tell us what is holding up your AI work.

Share the project, review, or decision you are working through.

M&S Consulting has worked with commercial and federal clients since 2002. We connect AI to enterprise systems and help teams implement, adopt, and operate it.