AI consulting services anchored on a fixed-fee one-week audit. Day 5, you get a written roadmap with named workflows, walk-away conditions, and a model recommendation grounded in your eval set. Not slides. Model-agnostic, operator-led, and openly benchmarked against Big-Four firms, freelancers, and in-house builds. Most teams start with the discovery audit.
AI consulting produces a ranked workflow list with per-workflow model recommendations, token-cost projections, eval-set designs, and a walk-away point for each. Eval sets typically use LLM-as-judge scoring against a golden set of 50-200 graded examples per workflow, sized so the regression bar is statistically meaningful before any code is written. Unlike management consulting (McKinsey, Deloitte, Accenture) which delivers strategy frameworks and change-management plans, AI consulting produces shipped engineering artifacts and runnable evals. Unlike a SaaS vendor "AI readiness assessment" which is pre-sales for that vendor product, honest AI consulting is model-agnostic and includes "when not to build" as a valid outcome. A typical engagement is a 1-2 week audit ending in a written roadmap and one of three decisions: pilot, defer, or kill.
Our AI consulting firm runs the same engagement model as our build practice. Start with the audit, ladder into delivery only if the data says go. Most teams start with the discovery audit; about a third move into a pilot inside the quarter, and the second workflow is always cheaper than the first.
One week. fixed-fee. Four stakeholder interviews, a data-readiness pass on the systems you care about, eight to twelve workflows plotted on the effort × value matrix, and a written 90-day roadmap on Friday. You leave with the ranked list. Build with us, build in-house, or hire someone else. Most teams start here.
If the audit surfaces a workflow you want shipped, we move into a fixed-price pilot: four to eight weeks, fixed-bid depending on scope. AI implementation consulting wired to your real systems, with a kill point at week two if the metric won't move. The audit's go / no-go is the contract baseline.
Once you have one workflow live, the second is cheaper than the first. From monthlynth, we run a quarterly strategy refresh, monthly drift + cost-of-ownership reporting, and embedded delivery on the next two or three workflows on your roadmap. Cancel any month.
An AI consulting company is judged on the artefact it leaves behind. These are the six workstreams the audit covers, every time: AI readiness assessment, use-case prioritization, model selection, governance, roadmap, and maturity benchmark. None of them get separated into 'phase 2.'
Data, talent, tooling, governance. We score the systems you'd actually pipe AI into (CRM, support tooling, ERP, BI) against a four-dimension readiness rubric. Honest scoring; a 3/5 means "workable with caveats," not "we'll fix it later."
Effort versus value on the workflows you raised in discovery, plus the ones we add. Each use case gets a data-readiness call, a time-to-pilot range, a cost band, and an explicit walk-away condition. No "phase 2" hand-waving.
Claude, GPT, Gemini, open-weights, or a hybrid. We benchmark on your eval set, not the marketing chart. AI vendor selection consulting where the recommendation comes with the token-cost math, and the reason a cheaper model would have worked. AI implementation consulting follows the same eval discipline once the vendor decision is locked.
Where generative AI fits in your business, where it doesn't, and the guardrails your security, legal, and compliance teams will ask for. DPIA template, prompt-injection threat model, audit-logging architecture. Written, not gestured at.
Written 90-day roadmap with three to five named workflows, ranked, plus ai tco modeling per workflow (token cost, integration cost, change-management cost, opportunity cost of NOT building). Realistic time-to-value grounded in our shipped pilots. The ai strategy consulting artefact your CFO and your steering committee will actually read.
Where you are on a five-tier maturity model versus comparable mid-market peers. Not a vanity score. A delta list that maps to the roadmap and tells you the order in which to fix things.
The fixed-fee audit is not a discovery deck. It is a five-stage pipeline with a named output every day, a confidence score we share with you on Friday, and a written go / no-go on every workflow we surfaced. Run end-to-end in one calendar week.
The audit's primary deliverable is a written 90-day roadmap with three to five workflows, sequenced, with kill-points and cutover dates. Here's a sample — your workflows replace ours, the dates anchor to your kickoff week.
Weeks 1–8
→ continuous · $5K/mo from week 9
Weeks 3–10
→ continuous · $5K/mo from week 11
Weeks 5–12
Weeks 9–12
Sample 90-day roadmap. Every audit produces one of these — your exact workflows, dates, and milestones replace these placeholders.
Every workflow we surface in discovery is plotted here on the third day of the audit. The matrix is the artefact you take into your steering meeting — not a generic 2×2, but eight patterns we have already shipped, scored against your data and your stack. Tap a dot for the audit findings we would write on day 4.
Scoring is per-engagement. Anonymized averages shown. Your matrix on Friday will have your workflow names + your readiness deltas.
Four real options for an AI consulting engagement, or ai business consulting if your CFO is the one signing. The Big Four (BCG, McKinsey, Accenture, Deloitte) run the partner-led playbook. Freelancers from Upwork or Toptal cover narrow technical questions. An in-house head of AI is the long-game answer. Our audit-led model sits in between. None of these are wrong. They are different shapes of the same need. Here is when each one wins.
Big-Four pricing reflects public partner-led-engagement ranges in the AI strategy practice. Freelancer ranges based on Upwork + Toptal vetted-rate medians for senior AI consultants. In-house compensation reflects mid-market US head-of-AI salary bands.
Twenty-minute fit call. We will tell you when your problem is squarely in the Big-Four lane or when a freelancer would do the job in two weeks for less. No deck, no obligation.
The audit is not a stand-alone slideware engagement. It is the first phase of the same pipeline that ships the pilot and runs the continuous partnership. Same team, same kill conditions, same operator depth. AI implementation consulting ladders out of the audit's roadmap; nothing else.
fixed-fee. Five-day pipeline from stakeholder discovery through to a written roadmap. Goal: a defensible decision artefact you can take into your steering meeting.
If the audit surfaces a workflow worth shipping, we scope the pilot together. Eval-set design, model selection, integration boundary, kill conditions for week 2. Fixed-price quote before any build kicks off.
Four to eight weeks of build against your real systems. Eval-tested before launch, shadow-mode against your current process, deployed behind a feature flag. Walk-away point at week 2 of the build if the metric won't move.
Continuous AI consulting on the next two or three workflows. Monthly cost-of-ownership and drift reporting. Quarterly maturity-assessment refresh so the roadmap stays current as the model landscape shifts.
Most engagements that go past the audit ship a pilot. Some get killed at day 5, and that's a feature, not a bug. Here's the honest decision graph from the moment you book a discovery call.
Animated graph fires one step at a time. Day-5 verdict is the explicit branch point: kill, defer, or ship.
Same pricing as our other AI services pillars. The audit is the entry point; about 60% of teams move into a pilot inside the following quarter, and most pilot clients stay on a continuous partnership for the next two or three workflows.
Five-day, fixed-fee audit that ends with a written roadmap, not a slide deck.
Ship the top use case the audit surfaced. Fixed price, kill point at week two.
Embedded consulting + delivery on the next workflows on your roadmap.
After the audit, workflows route to the specialty team best suited to ship them — sometimes that's us, sometimes it's your in-house team, sometimes it's a sibling team in our practice. The audit produces the routing decision; we are honest about which team should ship each workflow.
Routing decisions live in the day-5 roadmap. Most audits route 1–2 workflows to a sibling team and 1 back to the in-house team.
Anonymized capability patterns drawn from real audits. The point of each one is what we recommended, including the engagements where the day-5 answer was 'don't ship that workflow.' Named references shared under NDA once we know what you are evaluating.
Inbound team had built a GPT-3.5 lead-qualification agent that worked in demo and stalled in production. CFO had paused the budget; head of revenue wanted it salvaged. No one had written down what 'works' meant.
We ran the 1-week audit. Discovery showed the agent had no eval set and three competing definitions of a qualified lead. Day 3 matrix put lead-scoring at low-effort / high-value. Day 5 roadmap recommended a Sonnet-based shadow pilot against the existing rules engine, with an 8% lift threshold as the walk-away.
Board had mandated 'a generative AI strategy by Q3.' Ops director was wary of vendor pitches. Support team had been pitched three competing GenAI tools and didn't know how to evaluate any of them.
The audit surfaced 11 candidate workflows and killed 6 at day 3 (poor data readiness, or better solved with non-AI tooling). Roadmap picked two: document extraction for proof-of-delivery scans, and an internal-ops RAG agent over the dispatch handbook. Both shipped inside one fixed-bid pilot envelope.
Customer-service VP wanted a voice agent in production by end of year. Audit was scoped to confirm feasibility, model selection, and compliance posture before any build started.
Audit surfaced voice-agent as high-value but high-effort, with two unresolved blockers: call-recording retention required legal sign-off, and latency targets implied a hosting choice the security team hadn't reviewed. Day 5 roadmap deferred the voice-agent pilot by one quarter and shipped compliance doc review first as the lower-risk pattern. VP signed off and preferred a delayed, defensible roll-out to a fast, risky one.
Book the fixed-fee AI audit. Five days, four to six stakeholder interviews, data-readiness scoring on the systems you care about, eight to twelve workflows plotted on the effort × value matrix, and a written 90-day roadmap on Friday. No deck. No obligation to build with us.
AI consulting often ladders into a Claude or OpenAI build, into integration work, or into wider AI automation. These pages go deeper on each lane the audit might land on.
Multi-step autonomous agents with LangGraph + tool use.
Workflow automation: where the audit roadmap lands once shipped.
Plug AI into Salesforce, NetSuite, Slack: the cross-cluster build piece.
Hire healthcare AI engineers for ambient scribes, prior-auth, and EHR integration.
Legal AI audit + roadmap with privilege-ring mapping before any build.
When the consulting roadmap recommends conversational AI as the first ship.
Build-vs-buy audit when you're choosing between Glean, Notion AI, and a custom RAG knowledge base.
When the consulting roadmap recommends voice (often it does not — we will tell you). Sub-second voice on OpenAI Realtime API, chained STT-LLM-TTS, or Deepgram Voice Agent.