Most AI consulting engagements end with a $300K PowerPoint deck and zero working code. Clarista combines AI strategy with production delivery — you get a prioritized AI roadmap plus a working pilot on your cloud in 4-6 weeks. Fixed-bid from $50K. Senior engineers, not first-year MBAs.
The Big-4 AI consulting model is broken for production AI. Three reasons your last engagement didn't move the needle:
Big-4 generative AI consulting engagements bill $300K-$1M for the strategy, then another $500K-$2M for the build. Most of it pays for partner overhead and junior consultants, not engineering.
Workshops, interviews, frameworks, maturity models, capability assessments. The deck lands month 4. The pilot — if it ever starts — lands month 9. By then the market has moved.
Industry studies show only 30% of AI/ML projects make it from PoC to production. When strategy is decoupled from delivery, the gap is usually fatal.
We collapse strategy + build into one engagement. Roadmap and working code, same team, 4-6 weeks.
Pick the depth that matches where you are. Most clients start with Strategy + Pilot — strategy alone rarely justifies the spend without proof of build.
For teams that need clarity before committing capital. Opportunity assessment, use-case prioritization, build/buy/partner framework. No build.
Everything in Strategy Sprint, PLUS we build the top-priority use case as a production pilot on your cloud. You leave with strategy AND code.
Fractional CTO-level AI guidance for ongoing decisions. Senior architects plug into your leadership cadence.
Concrete deliverables, not "thought leadership." Every Strategy + Pilot engagement ships these:
10-30 use cases ranked on revenue impact, cost savings, build effort, model fit, data readiness, compliance risk.
Per use case: build in-house, build with Clarista, buy off-the-shelf, or wait. With the math behind each.
Quarterly sequencing with dependencies, capacity model, hiring needs, vendor needs, budget by quarter.
Reference architecture for your top use case. LLM selection. Data pipeline design. Governance model.
The top-priority use case, built end-to-end, deployed to your cloud, governed, ready for real users.
SOC 2 / HIPAA / ISO 27001 control mappings, data flow diagrams, security review artifacts.
The honest math when you compare a 4-week Clarista engagement to a 12-week Accenture / Deloitte / McKinsey engagement on the same scope.
| Clarista | Big-4 (Accenture, Deloitte) | McKinsey / BCG / Bain | Boutique AI Consultancy | |
|---|---|---|---|---|
| Time to roadmap | 2-3 weeks | 8-16 weeks | 10-26 weeks | 4-8 weeks |
| Working pilot included | Yes — in 4-6 weeks total | Add-on, separate $500K+ engagement | No — partners refer to delivery firms | Sometimes — varies |
| Cost (strategy) | $50K fixed | $200K-$600K | $500K-$2M | $50K-$200K |
| Cost (strategy + pilot) | $90K-$150K fixed | $700K-$1.5M T&M | $1.5M-$4M T&M | $150K-$500K |
| Pricing model | Fixed-bid only | T&M, scope-creeps | T&M with partner premium | Varies |
| Engagement team | Senior AI engineers + architects | 1 partner + 3-6 juniors | 1 partner + 4-8 MBAs | 1-3 senior generalists |
| Deliverable type | Roadmap + working code | 200-page deck + recommendations | Slide deck + framework | Deck + sometimes PoC |
| "Did anything ship?" | Yes — pilot in production | Maybe — separate engagement | Rarely — they don't build | Sometimes |
No multi-week "discovery" phase billed at $30K. Straight to substance.
2-day workshop with your leadership + tech team. Stack, data, constraints, ambitions, compliance landscape mapped in 1 week.
Scored use-case backlog, build/buy/partner framework, 12-month roadmap, architecture options. Working session to pick the pilot.
Senior engineers build the top use case end-to-end on Clarista platform, deployed to your cloud, governed by SOC 2/HIPAA/ISO.
Pilot in production. Full documentation pack. Roadmap signed off. Decision on next phase — scale, hand off, or stop.
We're built for teams that intend to actually BUILD. Minimum engagement: $50K.
If you need a 200-page strategy document for a board meeting and don't care whether anything ships — hire Accenture or Deloitte. If you need a thought-leadership white paper for marketing — hire a boutique. If you need a McKinsey-branded deck for political cover — pay the McKinsey price.
Right fit: CTOs, Chief AI Officers, and Heads of Innovation at mid-market and enterprise companies who have real budget, real intent to build, and have been burned by a previous Big-4 AI engagement that produced a deck and no working code.
All anonymized under NDA. Specifics shared on the scoping call.
Replaced a $480K Deloitte engagement with $135K Clarista Strategy + Pilot. Roadmap delivered week 2, working pilot live week 5. 40 analysts using it on day 1.
McKinsey scoped a 14-week $850K strategy engagement (no build). We delivered the strategy + a production claims triage agent for $110K in 5 weeks.
$50K, 2 weeks. Scored 24 candidate AI use cases. Recommended starting with 2 (regulatory doc analysis, KOL identification). Team then built in-house with our roadmap as the guide.
Anonymized to protect customer confidentiality. References provided in your industry on the scoping call.
Three structural differences. They sound small. They compound massively.
Big-4 generative AI consulting teams are typically 1 partner + 3-6 first-year consultants billed at senior rates. Most have never shipped production AI. Our teams are senior AI engineers (5+ years production) plus a solutions architect. The person scoping the engagement is the person writing the code.
The Big-4 model deliberately splits strategy from build because they bill twice. Strategy team writes the deck, build team gets re-handed the project (with all context lost) and re-discovers everything. We do both with the same team — strategy informs build, build pressure-tests strategy. The roadmap is realistic because the people writing it are the people who'd ship it.
Big-4 engagements are T&M because their estimates are bad and they bill the slippage. Fixed-bid means we own the risk. If we underestimate, we eat it. This forces us to scope tight — and the result is a tighter, more useful strategy.
20-minute scoping call. Bring your AI ambitions, your stack, your team's reality. Leave with a fixed-bid number and a 4-6 week delivery date.
Book scoping call →Three differences. (1) We ship, not slide — every engagement ends with a working production pilot, not a PowerPoint. (2) Fixed-bid from $50K — no T&M scope-creep, no partner-overhead markup. (3) Senior AI engineers on the engagement, not first-year MBAs. Big-4 charges $300K-$1M for a 12-week strategy engagement. We deliver strategy AND working code in 4-6 weeks for $90K-$150K.
Week 1-2: AI strategy sprint — opportunity assessment, use-case prioritization, build/buy/partner framework, architecture options. Week 3-6: build the top-priority use case as a working production pilot on your cloud, governed by SOC 2 / HIPAA / ISO 27001. You leave with the roadmap AND a live AI app.
Three tiers. Strategy Sprint (2-3 weeks, no build): $50K fixed. Strategy + Pilot (4-6 weeks): $90K-$150K fixed. Embedded AI Advisory (monthly): from $25K/month. Compare to Big-4 generative AI consulting engagements at $300K-$1M, or McKinsey AI strategy at $500K-$2M for the same 12-week scope.
Both, but mostly generative AI in 2026 because that's where production demand is. AI/ML consulting (classical ML, recommendation systems, forecasting) is still meaningful, usually in finance, insurance, and supply chain. We scope each engagement based on what your problem actually needs, not what's hot.
Every engagement starts with a 2-week deep-dive into your stack, data, team skills, compliance constraints. The roadmap output is specific to YOUR situation — what to build first, what to buy, what to skip, what to defer. Not a generic "top 10 AI use cases" deck.
Yes — that's the whole point. The pilot is built on production-grade infrastructure from day 1. When you decide to scale, no rewrite needed. We can continue building under our AI Development Services, hand off to your team (Build-Then-Train), or hand off to a vendor of your choice.
That's exactly when AI consulting makes sense. Start with our 2-3 week Strategy Sprint — we assess the opportunity space, score use cases on impact/effort/feasibility, and recommend the top 1-3 to build. You leave with a prioritized roadmap. Then decide whether to build with us or take it back in-house.
AI consulting under $50K, projects with no intent to actually build, or change-management-only engagements aren't a fit. If you need a 200-page strategy document for a board meeting and don't care if anything ships, hire a Big-4. If you want to KNOW what to build AND see it work, that's us.
Yes — our Embedded AI Advisory. Senior architects plug into your weekly leadership cadence: AI roadmap reviews, build-vs-buy decisions, vendor evaluations, technical architecture, hiring panels. Monthly retainer from $25K. Most clients use this for 3-6 months while their internal AI capability builds up.
If you're evaluating AI consulting services, generative AI consulting companies, or AI/ML consulting firms, here's what actually matters.
AI consulting in 2026 means three different things depending on who's selling. Big-4 firms (Accenture, Deloitte, IBM, EY, PwC) sell "AI transformation consulting" — change management, capability assessments, governance frameworks. Strategy firms (McKinsey, BCG, Bain) sell "AI strategy" — board-level prioritization decks, market analysis, business case modeling. Boutique AI consultancies sell technical AI/ML consulting — architecture design, model selection, technical roadmaps. Each has its place. None of them ship code as part of the engagement (mostly).
The 2026 generative AI consulting market is roughly $15B and growing fast. The questions that matter when evaluating a generative AI consulting company: (1) Have the consultants personally shipped production LLM apps? (Many haven't — generative AI is too new.) (2) Do they bring engineering capacity or just slides? (3) What's their LLM-vendor stance — agnostic or locked into one provider? (4) Will they recommend "build" if it's better, or only ever "consult"? (5) Is the pricing fixed-bid or T&M?
Classical AI/ML consulting (recommendation systems, demand forecasting, fraud detection, predictive maintenance) is still a meaningful chunk of the AI services market. If your problem is well-suited to traditional ML — large structured datasets, well-defined target variable, repeated decisions — AI/ML consulting is often better than generative AI consulting. Don't pick the trend; pick the right approach for the problem.
The most common failure modes we see in AI consulting engagements: (1) strategy deck that overestimates impact and underestimates technical lift, (2) recommendation that requires hiring a team that takes 12 months to build, (3) build-vs-buy framework that ignores total cost of ownership, (4) governance / compliance treated as an afterthought, (5) no real pilot — just "we recommend doing a pilot in Q3." The cure to all five: collapse strategy and execution into one engagement with one team accountable for both.
Most AI consulting engagements need to be followed by 3-9 months of build to test whether the strategy works. Platform-backed consulting (Clarista's model) collapses that to 3-4 weeks because the production AI infrastructure — auth, governance, observability, multi-LLM orchestration, eval framework — is already built. Strategy can be pressure-tested against a working pilot in 4-6 weeks instead of 4-6 months. Talk to our team →
20-minute call. Bring the AI ambitions, the stack, the budget. Leave with a fixed-bid number and a 4-6 week delivery date — strategy AND working pilot.
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