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AI Consulting & Strategy

AI Consulting That Ends in Production, Not Slides

Operational discovery, readiness assessment, use-case selection, and an architecture your IT team can review, delivered by engineers who then build and operate the result. The output of DPI consulting is a scoped deployment with a metric, not a strategy deck.

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Who This Is For

Built for leaders who need a credible first deployment

  • Owners and COOs who know AI should help operations but have not seen a proposal that names the workflow, the system, and the number.
  • Companies that ran a pilot that never reached production and want to understand why before spending again.
  • IT and compliance leaders who need the data, hosting, and governance questions answered before anything is built.
  • Private equity operating partners assessing where AI pays off across several portfolio companies.

What Consulting Delivers

Concrete outputs at every step

Operational discovery

Forward-deployed engineers map your highest-volume workflows with the people who do the work: steps, systems, volumes, wait times, and error costs.

AI readiness assessment

Data quality and access, system integrations, security and compliance constraints, team capacity, and the gaps to close before deployment.

Use-case selection and ROI model

Candidates ranked by impact, feasibility, and risk, with an estimate of hours returned, response times, or revenue protected for each.

Architecture and hosting plan

Model choices, integration design, data flows, guardrails, escalation, and whether to run hosted, in your cloud, or fully self-hosted.

Deployment roadmap

A sequence of scoped deployments with owners, timelines, success metrics, and the governance model that keeps them accountable.

Pilot rescue

For stalled projects: a diagnosis of why the pilot did not reach production and a plan to get it there or replace it.

Why so many AI initiatives stall

The pattern is consistent: a vendor demo, a pilot on a convenient use case, and then nothing. The pilot never had a metric, the integrations were left for later, the data was not ready, and nobody owned the system after the consultants left. Strategy decks do not fix that; scoping does.

DPI consulting exists to produce one thing: a first deployment that is worth doing and that will reach production. We get there by looking at the work, not the technology. Where does volume pile up, what does a mistake cost, which systems hold the truth, who has to approve, and what is the number that would prove success.

Discovery by engineers

Our discovery is forward-deployed: engineers sit with the people who take the calls, process the documents, and assemble the reports. They document steps, systems, volumes, and wait times, and they collect real samples. That is why the resulting architecture is specific enough to build from and the ROI model is grounded in your volumes rather than industry averages.

Readiness and architecture

The readiness assessment answers the questions that decide whether a deployment survives: is the data accessible and good enough, which integrations exist, what compliance constraints apply, and where will the models run. The architecture then makes concrete choices: hosted models from OpenAI, Anthropic, or AWS Bedrock, or self-hosted open-source models such as Qwen; telephony on Asterisk for voice work; orchestration with LangGraph; PostgreSQL and vector stores for knowledge; guardrails and human review points. Your IT and compliance owners review it before anything is built.

The roadmap you receive

A sequence of scoped deployments, each with a workflow, integrations, a success metric, a timeline, and an operating model. The first one is scoped in enough detail to start immediately. If you continue with DPI, the same engineers build and run it. If you do not, the plan is written so someone else can.

How It Works

How a consulting engagement runs

  1. Kickoff and access

    Goals, constraints, stakeholders, and access to the systems and people involved. NDA and, where relevant, BAA signed.

  2. Discovery on the floor

    Engineers observe and interview the teams that run the workflows, pull volumes and samples, and document the current state.

  3. Assessment and design

    Readiness findings, ranked use cases, architecture options with trade-offs, and hosting and compliance recommendations.

  4. Roadmap and decision

    A written roadmap with the first deployment fully scoped: metric, integrations, timeline, and what it takes to run it afterwards.

Stack & Integrations

What we assess and design for

OpenAI, Anthropic Claude, AWS Bedrock Self-hosted Qwen and open-source models Open-source speech models and Asterisk telephony LangChain and LangGraph orchestration PostgreSQL, pgvector, Qdrant, Redis CRM, ERP, ticketing, and document systems AWS, Kubernetes, Docker, Cloudflare HIPAA with BAA, access control, audit trails

Industries

Consulting by industry

Real Estate

Lead handling, leasing operations, maintenance, and portfolio reporting.

Private Equity

Portfolio-wide assessments and repeatable deployment playbooks.

Manufacturing

Quality, procurement, and production coordination workflows.

Financial Services

Onboarding, document review, and compliance workflows with private hosting.

Engagement Models

Engagement models

AI operations audit

A short, fixed-scope assessment of one business unit: workflow map, ranked opportunities, and the first deployment scoped.

Discovery and roadmap

Two to four weeks across the business: readiness assessment, architecture, hosting and compliance plan, and a sequenced roadmap.

Fractional AI leadership

Ongoing advisory for companies rolling out several deployments: prioritization, vendor and model decisions, governance, and reviews.

FAQ

Questions about AI consulting

How is DPI consulting different from a strategy firm?

The people doing the discovery are the engineers who will build and operate the system. Recommendations are limited to what we would put into production ourselves, and every deliverable names the workflow, the integrations, and the metric.

Do we have to build with DPI afterwards?

No. The roadmap and architecture are yours and are written so an internal team or another vendor can execute them. Many clients do continue with us because the same engineers already understand the workflow.

Do you work on a fixed price?

Yes, for everything with a defined output. Discovery, readiness assessment, architecture, and roadmaps are fixed-scope engagements quoted in writing before they start, so the number does not move while the work runs. Open-ended advisory retainers are the exception we avoid, because they reward hours rather than decisions.

What does AI consulting cost for a small business?

Less than the enterprise figures you see quoted, because the scope is smaller: one or two workflows, a handful of systems, and a decision about what to build first. A scoped discovery for a company with twenty to a hundred employees is a fixed fee in the low thousands, and it ends with an architecture and a build estimate you can take anywhere. Our AI consulting cost guide explains the pricing models.

Do you advise on AI governance and policy?

Within the scope of a deployment: access control, data retention, human-in-the-loop rules, audit trails, model and vendor choice, and the documentation your security or compliance team needs to approve it. We do not sell standalone governance frameworks; the policy is written against systems that are actually going live.

How much does AI consulting cost?

The audit and the discovery engagements are fixed-scope with fixed pricing quoted after a short call about your size and goals. Fractional leadership is a monthly arrangement. We do not bill open-ended hours for discovery.

What do you need from us?

Access to the people who run the workflows, samples of the inputs they handle, volumes, and a conversation with IT about systems and data. A few hours per week from a sponsor keeps the engagement on schedule.

Can you assess a project that already stalled?

Yes. Pilot rescue is a common starting point: we diagnose why the pilot did not reach production, usually integration, data, or governance gaps, and propose the shortest path to a working system.

How do you handle confidentiality?

NDA before discovery, BAA where health information is involved, minimum-necessary access to systems, and deliverables that stay your property.

Related

Next Step

Bring one workflow. Leave with a production plan.

Tell us where calls, tickets, documents, or approvals pile up. We map the workflow, size the impact, and propose a deployment you can measure.

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