Everything it takes to make AI real — under one roof.
Four connected practices, backed by management-consulting judgment and deep expertise across data science, machine learning, computer vision and NLP. Engage one, or let us lead an end-to-end AI-driven digital transformation — from boardroom strategy through a system your team runs in production.
AI Strategy & Digital Transformation
Cut through the noise and turn AI ambition into an operating reality. With a management-consulting lens, we help leadership find where AI genuinely creates value, make the strategic and tactical calls, then lead the digital transformation to capture it — across strategy, data, process, and people.
- ▸ AI opportunity assessment & roadmapping
- ▸ Digital transformation & operating-model design
- ▸ Data & platform modernization strategy
- ▸ Process automation & workflow redesign
- ▸ Build-vs-buy, model selection & responsible-AI governance
- ▸ Executive & team enablement to make change stick
- ▸ AI-native product design & prototyping
- ▸ RAG, search & knowledge systems
- ▸ Agentic workflows & automation
- ▸ Evaluation, guardrails & observability
- ▸ Production deployment & scaling
AI Products & Platforms
We design and build AI products end to end. From the first prototype that proves the idea to a hardened platform with the evaluation and monitoring that keep it trustworthy in the wild.
Applied AI Research
The gap between a promising paper and a dependable product is where projects die. We do focused, reproducible R&D on exactly those problems — and hand you results you can build on.
- ▸ Retrieval & grounding quality
- ▸ Agent reliability & evaluation harnesses
- ▸ Fine-tuning & domain adaptation
- ▸ Benchmarking & model comparison
- ▸ Prototyping emerging techniques safely
- ▸ Senior AI engineers embedded in your team
- ▸ Data pipelines & feature infrastructure
- ▸ MLOps, CI/CD & model lifecycle
- ▸ Integration with your existing stack
- ▸ Mentoring so your team can carry it forward
Embedded Engineering
Sometimes you don't need advice — you need senior hands. We embed with your team to accelerate delivery and build the unglamorous infrastructure that makes AI reliable at scale.
From first strategy to governed production.
We cover the whole lifecycle — so nothing falls through the cracks between the advisors, the designers, and the engineers. Because it's one senior team, it actually connects.
AI Strategy
Pinpoint where AI creates durable advantage, with the business case to back the investment.
Roadmap & Prioritization
A sequenced, costed plan — from quick wins to flagship bets — that leadership can commit to.
Product Design
Shape the AI product itself: user experience, workflows, and where humans stay in the loop.
Solution Architecture
The system, data, and model architecture to build it scalably, securely, and safely.
Implementation & Delivery
Senior engineers build, integrate, and ship it to production — not slideware, working systems.
Product & Strategy Consulting
Ongoing, hands-on guidance for product leaders and executives as you build and scale.
AI Governance & Responsible AI
Adopting AI without governance is a liability. We put practical controls in place — policy, model risk assessment, evaluation and monitoring, data protection, and responsible-AI practices — sized to your industry and regulatory context, so you can move fast and still stand up to scrutiny.
- ▸ AI policy, standards & usage guardrails
- ▸ Model risk, bias & safety assessment
- ▸ Evaluation, monitoring & audit trails
- ▸ Data privacy, security & compliance alignment
The disciplines behind the practices.
Whatever the engagement, it's delivered with genuine depth across the full data-science and machine-learning stack — not just the parts that are fashionable this year.
Data Science & Analytics
Statistical modeling, forecasting, and experimentation that turn messy data into decisions you can defend.
Machine Learning
Classification, regression, ranking, and recommendation models tuned for real production loads.
Deep Learning
Neural networks for the problems that need them — architecture design, training, and transfer learning.
Computer Vision
Image and video understanding: detection, segmentation, OCR, and automated visual inspection.
Natural Language Processing
Text and language at scale: extraction, semantic search, summarization, and understanding.
One connected stack: agentic applications on top, operated by the LLMOps, MLOps, and AIOps layers underneath — how modern AI actually reaches, and stays in, production.
Agentic AI
Autonomous, multi-step agents that plan, use tools, and coordinate — with deterministic control and human-in-the-loop guardrails.
LLMOps
Operating LLM and agent apps: prompt and context management, RAG, evaluation, guardrails, and cost & latency monitoring.
MLOps & Data Engineering
Pipelines, feature stores, and model-lifecycle tooling that keep systems reliable and observable in production.
AIOps
AI applied to running systems — anomaly detection, root-cause analysis, and automated incident response at scale.
Right-sized to where you are.
Discovery Sprint
A focused 2–4 week engagement to frame the problem, prototype a slice, and give you a clear, evidence-backed go/no-go.
Product Build
End-to-end design and delivery of an AI product or platform, from prototype to a production system your team owns.
Embedded Partner
An ongoing senior team alongside yours — advising, building, and leveling up your in-house AI capability over time.
Not sure which one fits?
Tell us the problem. We'll recommend the smallest engagement that gets you a real answer.