AI automation consulting
AI Automation Consulting That Ends in Production (Not in a Deck)
Most AI automation consulting engagements end with a recommendation. Ours end with a workflow running on your real data. Same team scopes the strategy, picks the architecture, designs the governance, and ships the production build — in 6-10 weeks, fixed-price, no handoff loss.
In one sentence
AI automation consulting that ends in production means strategy, architecture selection, governance design, and production build delivered by the same team in a single phased engagement (Discovery 2-3 weeks → Build 6-10 weeks → Run optional) — collapsing the handoff loss that kills 60-70% of AI initiatives between recommendation and deployment.
Key facts
- Engagement model
- Strategy + build, same team
- Discovery (strategy phase)
- $5-8k · 2-3 weeks
- Build (production phase)
- $15-40k · 6-10 weeks
- Run (advisory + ops)
- $2-6k/mo · optional
- Time to production
- 6-10 weeks from Discovery start
- Vendor referral fees
- None taken (honest model selection)
What we advise on
Six advisory areas covered in every Discovery. Each one informs the Build SoW with fixed-price, scoped engineering work.
AI strategy and roadmap
Which workflows to automate first, in what order, and why. We map your existing operations against an AI-readiness scorecard and produce a 6-12 month sequence with capital, team, and risk implications documented.
Architecture and model selection
We pick the model family (Claude, GPT, Gemini, or multi-LLM routing), the retrieval architecture (RAG, hybrid search, agentic), and the deployment surface (own infra, Vertex, Bedrock, OpenAI API) based on your specific cost, latency, and governance constraints.
Governance and AI RMF design
We map your AI workflow against NIST AI RMF (Govern, Map, Measure, Manage) and design the control stack: approved sources, prompt versioning, reviewer queues, audit logs, attestation cadence. Reviewable by your risk officer before any production launch.
Build-vs-buy decision
We help you decide whether to build in-house, work with an agency, or deploy a SaaS AI platform. Honest answer based on your team capacity, time-to-value pressure, and IP sensitivity — not on what we want to sell you.
Operating model design
How the workflow runs week-to-week: KPI dashboard structure, reviewer team sizing, escalation paths, prompt-refresh cadence, attestation schedule. The operating model is what makes AI survive past month three.
Procurement and vendor negotiation
If the right answer is a SaaS platform (Glean, Copilot, ChatGPT Enterprise), we help you scope the procurement, negotiate terms, and design the integration. We don't take vendor referral fees.
How our AI automation consulting differs
Side-by-side with a traditional AI consulting engagement (Big 3, digital boutique, or specialist firm). The biggest difference is what happens at the end of the strategy phase.
| Dimension | Traditional consultant | AI-Native Agency |
|---|---|---|
| Deliverable | Slide deck, recommendations, vendor shortlist | Working production AI workflow on your real data + the deck explaining why |
| Engagement length | 3-6 months strategy phase, then 'find a vendor' | 2-3 weeks Discovery → 6-10 weeks Build → optional Run. Production by week 10. |
| Pricing model | Hourly retainer or T&M, $250-700/hr | Phased fixed-price. Discovery $5-8k. Build $15-40k. Run $2-6k/mo. |
| What's tested | Hypotheses tested in slides; vendor demos curated to look good | Labelled test set of 200-1000 real cases; thin-slice shipped to production by week 6 |
| Outcome accountability | Best-effort recommendations; KPI ownership transferred to internal team | We baseline KPIs in Discovery, instrument them in Build, report weekly during Run |
| Vendor / model selection | Recommend a vendor; you negotiate, contract, integrate, operate | We pick the model architecture (Claude, GPT, Gemini) and own the build end-to-end |
| Exit | Engagement ends with the report; knowledge leaves with the consultant | All prompts, evals, code, runbooks handed over. Month-to-month Run, no lock-in. |
Frequently asked questions
What is AI automation consulting?+
AI automation consulting is advisory work on which business workflows to automate with AI, in what order, with what architecture, and under what governance. Traditional consulting stops at the slide deck. Our model continues into production: same team scopes the strategy AND builds the workflow.
How is your AI automation consulting different from McKinsey, BCG, or Accenture?+
Three differences. (1) Engagement length: 2-3 weeks Discovery vs 3-6 months strategy phase. (2) Deliverable: working production workflow + the deck vs the deck alone. (3) Outcome accountability: we baseline KPIs in Discovery and report against them weekly during Run; traditional firms transfer ownership to your internal team at the end of strategy. Pricing also differs by 5-15× per equivalent workflow.
How much does AI automation consulting cost?+
Phased fixed-price. Discovery (the strategy phase) is $5-8k for 2-3 weeks and includes workflow mapping, KPI baseline capture, risk model, architecture recommendation, and Build SoW. If you commit to Build, $15-40k for 6-10 weeks. Optional Run at $2-6k/month, month-to-month. Discovery is the only commitment to start.
Do AI automation consultants actually build anything?+
Some do. Most don't. The typical AI consulting engagement ends with a recommendation; you then hire engineers (or a separate vendor) to build. We close that gap: same team scopes the strategy AND ships the production workflow. Eliminates the handoff loss that kills 60-70% of AI initiatives between strategy and execution.
When should I hire an AI automation consultant vs an AI agency?+
Hire a pure consultant if you need brand-name cover for an investment decision (e.g. you need McKinsey's logo on the recommendation for the board). Hire an AI agency if you need the workflow actually built. Our model collapses both into a single engagement — strategy + build with the same team. Cheaper, faster, and the team that scoped the work owns the result.
What if I already have an internal AI team?+
Common pattern: we own Discovery and the operating-model design, your team owns the Build, we stay on as advisory during Run. The agency engagement front-loads the architecture decisions and reference implementations; your team takes them in-house and adapts. Documented in the Build SoW as a handover plan.
Start with strategy
Discovery is the strategy phase. $5-8k. 2-3 weeks.
Output: a 25-page strategy report, an architecture recommendation, a risk register, and a fixed-price Build SoW. The only commitment to start. After Discovery you can commit to Build, take the report in-house, or stop — your call.