AI consulting

From AI ambition to systems that run

We advise mid-market leaders on where AI creates measurable value, how to architect it on the OpenAI platform, and how to operate it inside an existing control environment. The work is senior, vendor-neutral on everything except evidence, and structured to hand off cleanly to your team.

Discuss an AI initiative

Common challenges

Why AI programs stall

The obstacles are rarely technical capability. They are decisions that were deferred.

Pilots that never reach production

A demo built in a week stalls for two quarters because nobody defined the data boundary, the approval path, or who owns the output when it is wrong.

Use cases chosen by enthusiasm

The first use case is usually the most visible one, not the most valuable one. Sequencing by value and feasibility changes the return of the entire program.

Unbounded and unpredictable cost

Token spend behaves like a variable cost with no ceiling until routing, caching, and context discipline are designed into the system.

Quality nobody can measure

Without an evaluation set, output quality is an opinion. Teams cannot tell whether a prompt change, a model change, or a data change made things better.

Security and compliance ambiguity

Legal, audit, and security teams block deployment when data flows, retention, and access controls are undocumented.

Shadow AI already in the environment

Employees adopt tools faster than governance arrives. Detection precedes policy, and policy precedes enforcement.

How we engage

Assess, architect, optimize

Three phases, each with defined deliverables. Engagements can start at any phase.

PHASE 01

Assess

We inventory candidate use cases, existing AI usage, data readiness, and the control environment. Each use case is scored on business impact, feasibility, data dependency, and risk. The deliverable is a prioritized roadmap with cost models and explicit success criteria.

Use case portfolio with scoring and sequencing
Data and retrieval readiness assessment
Shadow AI inventory and governance gap analysis
Cost model and target unit economics

PHASE 02

Architect

We select the architecture pattern before the engineering starts. Retrieval, structured extraction, workflow orchestration, and agentic execution are different systems with different failure modes. We document the pattern, the data flows, the control points, and the evaluation approach, then oversee delivery.

Reference architecture and data flow documentation
Model selection, routing, and fallback strategy
Evaluation harness and acceptance thresholds
Human-in-the-loop and approval gate design

PHASE 03

Optimize

Once a system is live, the work shifts to measurement and cost. We tune retrieval quality, right-size context, adjust routing between models, and monitor drift against the evaluation set. The operating model transfers to your internal team with documentation and runbooks.

Quality and cost monitoring against baselines
Retrieval and prompt tuning cycles
Runbooks, escalation paths, and ownership model
Knowledge transfer to internal teams

Solution patterns

Representative architectures

Pattern selection precedes engineering. These are the shapes most mid-market workloads take.

Enterprise retrieval and question answering

Grounded answers over contracts, policies, standards, and internal documentation, with citations and access control inherited from the source systems.

Document extraction and structured output

Converting unstructured intake, invoices, claims, and reports into validated structured records that downstream systems can consume.

Workflow automation with approval gates

Multi-step processes where the system drafts and routes, and a human approves before any consequential action executes.

Agentic operations with tool access

Bounded agents with explicit tool permissions, audit logging, and rollback paths for ticket triage, research, and operational tasks.

Security and technology operations assistant

A role-aware assistant that helps authorized teams use approved technical documentation, procedures, configurations, and operational information.

Executive decision support

Structured synthesis of trusted organizational information to support planning, risk evaluation, and leadership communication.

These are representative architecture patterns, not completed customer case studies.

Platforms we work across

Technology ecosystem

OpenAI APIs and ChatGPT
Microsoft Azure
Microsoft 365 and Entra ID
Microsoft Fabric and Power BI
Enterprise APIs and data platforms
Hybrid cloud and on-premises systems
Security and operational technology environments

Technology selections are based on customer requirements. References to third-party products do not imply endorsement, certification, or formal partnership.

Security by design

AI systems are in scope, not exceptions

Our security practice and our AI practice are the same practice. Controls are designed into the architecture rather than retrofitted after a legal review, which is a common cause of delayed deployment.

Aligned to NIST CSF 2.0, NIST AI RMF, CIS Controls v8, and ISO 27001

Data classification and boundary definition before any model call
Least-privilege tool and data access, inherited from existing identity controls
Prompt injection and untrusted content handling in retrieval pipelines
Full audit logging of prompts, tool calls, and consequential actions
Retention, residency, and vendor terms reviewed against contractual obligations
Model supply chain and third-party dependency review

Engagement structures

How the work is scoped

Fixed-scope assessments, delivery oversight, or ongoing senior leadership.

AI readiness assessment

A fixed-scope engagement producing a scored use case portfolio, readiness findings, and a funded roadmap.

Architecture and delivery oversight

Reference architecture, evaluation design, and technical oversight of internal or vendor delivery teams.

Fractional AI and security leadership

Ongoing senior leadership across AI governance, security posture, and executive and board reporting.

Want to discuss how these structural decisions apply to your environment? Contact us.