AI Business
Consulting
AI business consulting for businesses of all sizes, from owner-led firms to leadership teams. We find where AI returns the most in your operation, turn it into a plan with costs attached, then build it. A plan, not a slide deck.
Small business or startup? See AI consulting for small business →
Find out where automation pays before you spend anything building it.
Most AI strategy work produces a document. You pay for a study, receive a deck, and are left with the same problem you started with plus a plan you now have to find someone to execute.
We think the useful version answers three questions with numbers: which of your processes cost the most in hours and errors, which of those could realistically be automated, and what each one would be worth if it were. Anything beyond that is padding.
In practice, most clients learn more from our $5,000 pilot than from any assessment, because building one real thing surfaces the problems a study never finds. If you need the formal engagement for a board or a funding case, we do that too, but we will say when the pilot is the better buy.
What you actually get
- A ranked list of your processes by what they actually cost you
- A straight answer on which ones AI can help with and which it cannot
- A cost and a likely return for each, so you can prioritise honestly
- A 90-day plan someone can actually execute, not a slide deck
- A recommendation to do nothing, where that is the right answer
See what one pilot produced for a 40-doctor healthcare network: 85% of bookings automated.
Independently listed: Featured in Goodfirms' Top AI Companies in Florida (2026)
Everything below this point is the technical detail: the frameworks, models, and architecture we use. If that is not your area, skip it and send us a note instead.
What AI business consulting costs.
Free call
A 30-minute call to look at your workflows and tell you honestly whether AI fits.
Pilot
One fixed-scope workflow, built and running in about 14 days. Most projects fall between $5,000 and $15,000.
Retainer
Ongoing build and support for companies up to about fifteen people. Larger teams are scoped on the call.
Readiness and roadmapping are part of the project, not a paid report sold separately. See full pricing.
What an AI business consulting engagement covers.
Seven structured pillars — from bottleneck diagnosis and data architecture through governance, MLOps, and change management. Every pillar ends with an actionable deliverable, not a framework.
AI Readiness Assessment
We audit your data infrastructure, tech stack, and operational workflows to identify high-impact AI opportunities. This includes CRISP-DM process mapping, data maturity scoring, and vendor-neutral tool selection across OpenAI, Anthropic, and Google Gemini ecosystems. Our model selection guidance covers the current generation: Gemini 3.7 Flash for high-throughput agentic and coding tasks; Gemini 3.1 Pro for the most demanding reasoning, long-context document processing, and multimodal workflows; and Gemini 3.5 Flash-Lite for high-volume, cost-sensitive subagent tasks. The right model tier for each use case directly determines operating cost and system performance at production scale.
- Process & data gap analysis
- Vendor-neutral LLM evaluation incl. Gemini 3.7 Flash / 3.1 Pro
- ROI opportunity mapping
Strategic AI Roadmapping
We craft a phased 12-to-36-month adoption plan aligned with your KPIs. Roadmaps cover Agentic AI prioritisation, LLMOps toolchain selection (LangSmith, Weights & Biases, Arize AI), and governance under the EU AI Act and GDPR frameworks.
- Phased agentic rollout plans
- LLMOps observability strategy
- Compliance-first governance
Data Architecture & RAG Design
A robust AI strategy lives or dies on its data foundation. We design enterprise RAG pipelines using Pinecone, Weaviate, and pgvector, backed by FastAPI ingestion layers and Anthropic Model Context Protocol (MCP) integrations to connect you to live business data.
- Vector DB selection & design
- MCP-first tool integration
- Data sovereignty by default
Governance & Risk Management
We establish AI governance councils, bias monitoring pipelines, and audit logging frameworks. Our approach integrates with Microsoft Semantic Kernel and LangChain guardrails to enforce responsible AI in production, not just on paper.
- Bias detection pipelines
- EU AI Act compliance
- Audit-ready AI workflows
MLOps & Deployment Strategy
Transitioning from pilot to production requires engineering discipline. We implement MLOps pipelines with CI/CD for models, automated retraining triggers, and performance dashboards using Vertex AI, AWS SageMaker, and Azure ML.
- Model CI/CD pipelines
- Automated drift detection
- Vertex AI & SageMaker support
Change Management & AI Literacy
Technology without adoption is wasted investment. We run AI literacy workshops, establish internal AI champions programmes, and create prompt engineering guides tailored to your teams, ensuring your workforce amplifies AI rather than avoids it.
- Prompt engineering training
- Internal AI champions programme
- Executive AI briefings
SKILL.md Strategic Guardrails
We advise on the adoption of the 2026 SKILL.md open standard for enterprise AI. By standardizing how skills are documented and executed, you ensure your AI agents are reliable, auditable, and easily portable across your business units.
- SKILL.md adoption strategy
- Standardized skill documentation
- Auditable agentic workflows
What we build this on.
The platforms and models behind this service. We are vendor-neutral: each piece is chosen because it is the right fit for the job, and we move you when something better ships.
New models ship constantly. Keeping your systems current as they do is part of the retainer, not a change request you get billed for.
Strategy that leads to deployment.
Our consultants are practising AI engineers who ship production systems. That means every recommendation is grounded in what works at scale — and we can build it ourselves if needed.
We build it, then we keep it running.
What we deliver does not get handed over and forgotten. For one monthly fee we run it, fix it, adjust it, and move it onto newer AI models as they ship. No separate maintenance contract, no charge every time you want something changed.
We run what we built
Monitoring, alerting, and fixing it when something upstream changes.
Updates are free
Small changes and tweaks carry no development fee. You ask, we do it.
Model upgrades included
We move you to newer models when they ship. No migration fee.
Fixes aren’t billable
If something we built breaks, repairing it is not a new invoice.
Support on your channel
Slack, Teams, WhatsApp, email. Priority response under four hours.
New automation every sprint
Each month adds working automation, so the return compounds.
If we built it, keeping it working and keeping it current is already paid for.
Tools, proof and guides.
- → Pricing: pilots, retainers and what each includes
- → AI Readiness Score: a free five-minute check of where automation fits
- → Hire vs automate calculator: compare a new hire with automating the work
- → All case studies: systems we have built and what they changed
- → What a 14-day AI pilot actually looks like
- → How to tell if an AI agency can actually build it
- → AI automation agency vs in-house hire
- → How to implement AI in your business
Frequently asked questions.
What does an AI business consulting engagement actually include?
Our engagements are structured around seven pillars: AI readiness assessment, strategic roadmapping, data architecture and RAG design, governance and risk management, MLOps deployment strategy, change management, and SKILL.md standardization. Every recommendation comes with a build plan — not just a slide deck.
How is an AI consultant here different from a traditional management consultancy?
Our consultants are practising AI engineers who build production systems — not career consultants who have never shipped code. Every recommendation we make, we can also build. That means our advice is grounded in what actually works in production, not what looks good in a PowerPoint.
Do you offer machine learning consulting as well as general AI consulting?
Yes. Our machine learning consulting covers the full ML lifecycle — data preparation and feature engineering, model selection and fine-tuning, MLOps pipeline design, and production deployment. Machine learning consulting engagements are typically scoped after an initial AI readiness assessment.
How do you measure ROI on AI investments?
We establish baseline metrics during the assessment phase — processing times, error rates, labor costs, throughput volumes — then track improvements after implementation. Typical ROI metrics include: hours of manual work eliminated, error rate reduction, cost per transaction reduction, and customer satisfaction improvements. Clients see 30–60% operational cost reduction with payback within 3–6 months.
What does AI consulting cost?
We do not sell paid audits. The readiness and roadmapping work described on this page is the first phase of a project, not a product you buy on its own, so it is included in the engagement rather than invoiced separately. Almost everyone starts with our $5,000 pilot: one fixed-scope workflow, built end to end, with the before-and-after numbers measured, and the analysis happens as part of it. Ongoing retainers start at $1,500 a month and are sized to your company. If you want standalone advisory time for something we are not building, that starts at $150 per hour, but our builds, pilots, and retainers are never billed hourly. Your first 30-minute call is free.
Do I have to pay for an assessment before you will build anything?
No. The discovery phase is the technical and business analyst stage of your project, and it is where the project starts rather than a gate in front of it. You are not buying a report. You are starting the work, and the mapping and scoping are how we begin it properly.
How do I choose an AI consultant?
Ask three things before you sign. Can they build what they recommend, or will they hand you a report and leave? Will they show you a working system from a past client, not just a demo? And will they price the job both ways, what it costs done by hand against what it costs automated, so you can check the return yourself? A consultant who cannot answer all three is selling advice, not results.
Is AI business consulting worth it?
It is worth it when it ends in something running. Paid strategy work that produces only a document rarely pays back, because the hard problems show up during the build. That is why most clients start with a fixed-scope pilot: one real workflow, live in about 14 days, with the hours it saves measured against what it cost. If the numbers do not work, you find out for the price of a pilot, not a programme.
Do you work with small businesses as well as larger companies?
Yes. Retainers start at $1,500 a month for companies of up to about fifteen people, and the pilot is the same fixed price whatever your size. We have a dedicated page on AI consulting for small business that covers what owner-led firms usually automate first.
Thirty minutes.
We'll tell you exactly
where your ROI is.
No sales deck. No 50-page report you have to pay for before anything gets built. Just a direct conversation about which of your workflows are costing the most and whether AI can fix them. If there's no compelling answer, we'll say so. And it's a conversation with Kash, our founder, not a rep reading from a script, because the person who built this business is the one who should understand yours.