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Use cases ranked by value
Workshops that score opportunities on business impact, data readiness, and delivery risk — so you fund the right three, not a random thirty.
Services — AI & data
AI consulting that ends in production, not slideware.
We help CTOs and business leaders find the AI use cases worth funding, prove them fast, and industrialize the winners — with governance and ROI measurement built in from day one.
Why enterprises choose this service.
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Senior practitioners
Every engagement is led by engineers who have shipped production AI — not analysts reading from a framework.
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Governance from day one
Evaluation suites, human oversight, and audit trails designed in — essential for healthcare, finance, and government.
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Vendor-neutral advice
OpenAI, Claude, Gemini, or self-hosted — we recommend what fits your data, budget, and compliance posture.
How we deliver.
Step 01
Discover
Two-week assessment of your data, systems, and processes; a ranked use-case portfolio with business cases.
Step 02
Prove
A four-to-six-week pilot on real data with agreed success metrics — not a demo on toy examples.
Step 03
Industrialize
Production hardening: security review, evaluation pipelines, monitoring, and rollout plan.
Step 04
Scale
A repeatable operating model — platform, guardrails, and training — so your teams ship the next use cases themselves.
Technology we use.
OpenAIClaudeGeminiLangChainLlamaIndexPythonAzure AIAWS BedrockMicrosoft Fabric
Frequently asked questions.
How long does an AI readiness assessment take?
Typically two weeks: one for data and systems discovery, one for use-case scoring and roadmap. You get a written report with a ranked portfolio and indicative costs.
Do we need clean data before starting?
No. Data readiness is part of what we assess — most successful first use cases work with the data you already have, and the roadmap sequences data work realistically.
Can you work with our internal IT or data team?
Yes — most engagements are joint. We bring the AI engineering experience; your team keeps the institutional knowledge and owns the system after handover.
What does an engagement cost?
Assessments are fixed-price. Pilots and production builds are scoped per statement of work after the assessment — you always know the number before we start.
Related services.
In depth
AI consulting that ends in shipped systems, not slide decks
Enterprise AI strategy has a credibility problem: too many roadmaps, too few systems in production. Our AI consulting engagements are run by the same senior engineers who build — so every recommendation is grounded in what actually ships, secures, and scales.
A typical engagement runs in weeks, not quarters: use-case discovery across departments, data and platform readiness assessment, a value model that ranks candidates by ROI and risk, and an execution roadmap with named architectures. You leave with a prioritized portfolio — quick wins for momentum, platform bets for durable advantage — and the governance framework to run it responsibly.
Because we deliver generative AI, machine learning, and data platforms ourselves, strategy hands off to build without translation loss. Many clients start with a free AI readiness assessment and move straight into a first production sprint.
Engineer-led advice
Consultants who write architecture, not just observations — recommendations are buildable.
Value-ranked portfolio
Use cases scored by ROI, feasibility, and risk — you know what to fund first.
Strategy-to-build handoff
The team that plans is the team that ships — no agency gap.