AI Consultation Services Strategy from people who ship production AI.
AI strategy, opportunity assessment, build-versus-buy analysis, AI governance, and 12-to-24-month AI roadmap. Senior team. Fixed-scope engagements from 4 to 12 weeks. USD pricing.
We tell you which AI investments will earn back inside 12 months and which will not.
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Who we've built for.
How we work on AI consulting
- What we do
- AI opportunity audit · Build-vs-buy · AI governance · Roadmap · Vendor selection · PoC scoping · Org readiness
- Deliverables
- Opportunity matrix · cost-benefit per use case · roadmap · governance framework · PoC briefs · vendor shortlists
- Not what we do
- We do not write keynote slides. We do not write blogs. We deliver actionable artifacts the operating team uses.
- Engagement shapes
- AI opportunity audit (4 weeks) · AI roadmap (8 weeks) · AI governance (8 weeks) · Embedded AI advisor (12 weeks)
- Pricing in USD
- AI opportunity audit from $7,000 · AI roadmap from $12,000 · AI governance from $12,000 · Embedded advisor from $21,000
- Who delivers
- Senior practitioners who have shipped AI to production, not generalist consultants
Most AI consulting is generic, slide-heavy, and produced by people who have not shipped a production AI system. We deliver AI consulting from senior practitioners who have. Each engagement produces actionable artifacts: an opportunity matrix tied to revenue, a build-vs-buy decision per use case, a governance framework that fits your regulatory scope, and a 12-to-24-month roadmap that engineering can execute against. This page covers what we deliver, what we explicitly do not deliver, and what it costs.
Recent AI builds — named clients
Built a complete Legal AI Contract Review & Drafting platform from scratch, with LLM fine-tuning, MS Word add-in, and multi-dashboard ecosystem
Read case study →
All-in-one hospital platform with AI medical history in seconds, staff, patients, inventory, CRM & finance
Read case study →
Unified company knowledge graph, graph RAG, SOC/ISO PR scans & LLM implementation.md from every source
Read case study →
1.6B EAN product API, Next.js dashboard, Amazon/Walmart Chrome extension with Keepa charts
Read case study →What we deliver
AI opportunity audit (4 weeks)
Interview product, engineering, ops, marketing, support. Map use cases. Score by revenue impact and feasibility. Deliver an opportunity matrix, ranked, with cost-benefit per top 10.
Build-vs-buy assessment per use case
For each shortlisted use case: cost-benefit of build versus buy. Vendor shortlist. PoC brief with success criteria. We do not take vendor commission, so the recommendation is independent.
AI roadmap (8 weeks)
12-to-24-month sequencing. Dependencies, team and infrastructure investment, gating decisions. Tied to your engineering capacity and product priorities.
AI governance framework (8 weeks)
Acceptable use policy, model risk classification, evaluation gates, monitoring, incident response. Aligned to your regulatory scope (EU AI Act, NIST AI RMF, sector-specific).
Embedded AI advisor (12 weeks plus)
Senior practitioner embedded with your team. Architecture review, vendor selection, hiring panel, code review on AI components. 8 to 16 hours per week.
Related AI capabilities: AI & machine learning, AI chatbot development, Generative AI, Machine learning, Computer vision, NLP development, AI-powered software, Custom software development.
Use cases with cost ranges
AI opportunity audit for a 200-person SaaS
4 weeks. 25 interviews. 60 use cases identified. Scored by revenue impact and feasibility. Top 10 with cost-benefit. Recommended 3 for immediate PoC. Estimated combined first-year impact: $2.4M in revenue acceleration plus $480K in operational efficiency. Range: $7,000 to $12,000 depending on org size.
Build-vs-buy across 8 AI vendor decisions
6 weeks. Each use case assessed against a vendor shortlist plus a build option. TCO model per option over 3 years. Vendor lock-in and data residency assessed. Final recommendation: 5 buy, 2 build, 1 hybrid. Range: $8,000 to $14,000.
AI roadmap for an enterprise customer
8 weeks. 12-month and 24-month sequencing. Dependencies on data infrastructure, hiring, governance, vendor selection. Quarterly milestones. Tied to engineering capacity. Range: $12,000 to $21,000.
AI governance for a regulated fintech
8 weeks. Aligned to EU AI Act, NIST AI RMF, plus fintech-specific (model risk management, adverse-action notices). Policy, evaluation gates, monitoring, incident response. Range: $12,000 to $21,000.
How we run the engagement
Five-phase rhythm for AI consulting engagements. Every phase ends with a concrete artifact.
- Kickoff and discovery (week 1). Stakeholder interview round. Existing AI inventory. Regulatory scope. Output: interview synthesis plus scope confirmation.
- Investigation (weeks 2 to 4). Use case discovery via interview plus document review. Build-vs-buy analysis. Cost-benefit per option.
- Synthesis (week 4 to 6). Opportunity matrix. Recommendations. Roadmap. Governance framework.
- Review and iteration (week 6 to 7). Stakeholder review. Iteration on artifacts. Final sign-off.
- Handover (week 7 to 8). Final deliverables. PoC brief for top 3 use cases. Hand-over to engineering and product.
Tech stack
- We are stack-agnostic in consulting because the right stack depends on your team, your data, your regulatory scope, and your existing infrastructure. We assess what you have and what fits, not what we want to sell.
- LLM provider assessment: OpenAI, Anthropic, Google, AWS Bedrock, Azure OpenAI, Cohere, Mistral, plus self-hosted. We weigh on cost, latency, capability, data residency, contract terms.
- MLOps platform assessment: SageMaker, Vertex AI, Databricks, MLflow, Weights & Biases, self-hosted. Weighed on team capability, existing infrastructure, ongoing TCO.
- Vector store and RAG infrastructure: pgvector, Pinecone, Weaviate, Qdrant, Elasticsearch. Choice depends on scale, existing database, and team operational capability.
- Evaluation and observability: LangSmith, PromptLayer, Phoenix, Helicone, custom. Choice depends on workflow and existing observability stack.
- Governance tooling: Credo AI, Holistic AI, Fairlearn, internal frameworks. We do not require a tool, we require a process.
- Build-vs-buy framework: Used at every use case to evaluate vendor product maturity, total cost of ownership, vendor lock-in, customisation ceiling, time to value.
Pricing
AI opportunity audit
From $7,000
- 4 weeks.
- Opportunity matrix, build-vs-buy on top 5, PoC brief for top 3.
AI roadmap
From $12,000
- 8 weeks.
- 12-to-24-month sequencing tied to engineering capacity.
AI governance framework
From $12,000
- 8 weeks.
- Aligned to your regulatory scope. Policy, gates, monitoring, incident response.
AI build-vs-buy decision support
From $8,000
- 6 weeks.
- Vendor shortlists and TCO models for 5 to 8 decisions.
Embedded AI advisor
From $21,000
- 12 weeks. Senior practitioner embedded 8 to 16 hours per week.
- Architecture review, vendor selection, hiring panel, code review.
AI training workshop
From $5,000
- 2-day workshop tuned to your team.
- Live build exercise. Knowledge transfer with reusable templates.
FAQ
No. We do not resell, white-label, or take commission from any AI vendor. The recommendation in every engagement is independent. We tell you when off-the-shelf is the right answer even though it means a smaller engagement for us.