AI Consulting,
Delivered by Engineers.
Two decades of hands-on delivery experience at tier-1 telecoms and global enterprises. We combine executive AI advisory with real engineering — so you don't just get a strategy deck, you get working systems. From boardroom to production, without the AI-washing.
Why Most AI Initiatives Stall
Endless Experimentation
Dozens of PoCs, none in production. Teams cycle through tools and frameworks without converging on a roadmap that ties AI investment to measurable business outcomes. The issue isn't hype fatigue — it's the absence of a decision framework.
Strategy Without Engineering
Consultancies that write the deck but can't ship the system. You end up with a beautiful slide deck, an ambitious roadmap, and a development team left to bridge an unrealistic gap alone. The architecture doesn't match the strategy.
Vendor Lock-In & AI-Washing
Opaque pricing, proprietary platforms, and products labelled "AI" that are just dashboards with regression models. Most procurement teams have no framework to evaluate what they're actually buying — so they buy the deck, not the product.
Organisational Misalignment
Often the real blocker isn't data quality or model accuracy — it's that the organisation isn't ready to operate the system in production. Governance, ownership, and ways of working are usually the hidden constraint.
What We Do
Three consulting services built around a single principle: the strategy and the implementation must come from the same team.
AI & Data Strategy
Executive advisory, maturity assessment, and investment-ready roadmaps grounded in real feasibility.
Learn more ↓Prototypes & MVPs
Rapid working prototypes that validate commercial traction and technical feasibility together.
Learn more ↓Conversational Data Insights
LLM-powered interfaces that let non-technical teams query databases and get visual answers in natural language.
Learn more ↓Looking for DriftMind?
Our CPU-only, training-free streaming forecasting and anomaly detection engine is a separate product — not a consulting service. 33,000–48,000 predictions per second, agent-ready, deployable from SaaS to Raspberry Pi.
AI & Data Strategy
Despite years of experimentation, most enterprises still struggle to scale AI meaningfully. The issue isn't hype fatigue — it's that the path to value remains unclear. Too many initiatives focus on technology instead of outcomes, or leap into development without alignment, readiness, or feasibility. We help CxO and VP-level leaders adopt the organisational patterns that distinguish successful AI adopters from those stuck in endless experimentation. This service draws on over two decades of consulting and delivery experience.
What's Included
- Executive-level advisory to define a clear, organisation-wide AI strategy
- Design of investment-ready business cases grounded in real feasibility and ROI
- AI maturity assessments across six pillars: strategy, data, technology, people, vendors, governance
- AI ecosystem design — the right balance of internal talent and external partners
- Vendor selection frameworks to avoid lock-in and AI-washing traps
- Use Case Evaluation Framework (UCEF) to balance feasibility, impact, and market positioning
Our Differentiator
Unlike advisors who only produce slide decks, we combine deep technical acumen with strategic insight. Our frameworks are used by top-tier CTOs to:
- Move from intuition-based to data-driven decision-making
- De-risk AI investment by aligning with maturity and talent realities
- Identify use cases that deliver tangible outcomes, not more PoCs
- Architect the team, the partnerships, and the path to production
Our Strategy Methodology — 10 Weeks, 11 Deliverables
A structured program that takes you from ambition to an execution-ready portfolio. Fixed scope, fixed duration, defined deliverables at every stage.
Evaluation & Alignment
Advisory workshops with executives and key stakeholders
Establish the evaluation framework — ROI, feasibility, market and operational impact. Align leadership on what success looks like before any use case is picked.
Use Case Prioritisation
Assess and rank candidate use cases
Build a use case portfolio aligned with business strategy and goals. Apply the Use Case Evaluation Framework (UCEF) to balance technical feasibility, commercial impact, and market positioning.
Business Case Development
ROI models, feasibility analysis, and risk assessment
Technical and organisational requirements identified for each prioritised use case. Clear business cases with realistic investment and return envelopes.
Technical Feasibility
Validation without committing to full-scale build
Pathways for implementation explored with minimal risk. Vendor and technology identification. Pilot and PoC design with measurable validation plans.
Go-to-Market & Adoption
From strategy to operational transition
Vendors and internal resources identified as key parts of the transition. Operational transition plan ready for execution. Governance and operating model defined.
Weeks 11+
Execution & governance support
Hands-on support for Proof of Concept execution, governance, adoption, and monitoring. Many clients extend the engagement at this stage — we bridge directly into Prototypes & MVPs (our second service).
Custom Prototypes & MVPs
We believe the most effective way to bridge vision and execution is through focused, lightweight prototypes. These aren't just technical tests — they're strategic experiments designed to validate commercial traction and technical feasibility together. By building early, measurable artifacts, we help clients avoid premature scaling, de-risk investments, and build internal sponsorship. Often the real discovery is that organisational misalignment, not data quality, is the blocker to AI success.
What We Build
- Personalised recommendation engines from transactional data
- Anomaly detectors trained on your own historical data
- Conversational AI interfaces connected to live databases
- Forecasting and early-warning systems for operations teams
- Working PoCs, API endpoints, dashboards — real code, not slideware
Our Methodology
- Define: We work with you to define the core use case and success KPIs. What does "winning" look like in measurable terms?
- Iterate: We rapidly build and refine a minimum viable solution. Short sprints, real data, frequent check-ins.
- Deploy: We help you deploy on your infrastructure or via Thingbook's platform. Handover includes documentation, training, and a production-readiness checklist.
Typical Engagement
4 to 8 weeks from kickoff to working prototype. Fixed scope, fixed price. Joint delivery with your internal team wherever possible — knowledge transfer is part of the deliverable, not an afterthought.
Why It Works
A functional prototype is the fastest way to expose hidden assumptions, build internal sponsorship, and validate real commercial traction. It replaces months of debate with a working artifact stakeholders can actually try.
Conversational Data Insights
Turn any business query into a visual, contextual answer in seconds. We develop conversational insight engines that transform how non-technical teams interact with data. These aren't simple chatbots — they're AI-powered interfaces capable of answering domain-specific questions, generating SQL on the fly, retrieving relevant records, and visualising the results through charts and human-readable narratives. Executives, marketers, and operations teams can explore business KPIs by asking questions in natural language. It dramatically reduces dependency on analytics teams and shortens decision cycles.
What's Included
- Foundation-model and cloud-agnostic design — no vendor lock-in
- LLM-powered interfaces over SQL databases and data lakes
- Retrieval-Augmented Generation (RAG) pipelines with vector embedding stores
- Auto-generated charts via ECharts, D3, or your existing BI tooling
- Human-readable explanations and visual storytelling layered over raw results
- Row-level security and query governance baked into the agent layer
Example Use Cases
- Marketing teams exploring customer behaviours without writing SQL
- Operations teams querying KPIs and system health without engineering tickets
- Executives receiving daily briefings from a conversational dashboard
- Product managers analysing adoption funnels in natural language
- Support teams exploring case patterns to surface common failure modes
Industries We've Delivered In
Our team has delivered AI, data engineering, and consulting projects across five industries over two decades. Specific client names are held in confidence; industry references are available on request.
Agent-Ready by Design
Every system we deliver is designed to be consumed by AI agents — not just humans and dashboards. That includes MCP tool endpoints, A2A Agent Cards, and OpenAPI specs ready for auto-discovery. Your analytics infrastructure becomes part of any AI agent's toolkit.
MCP
Model Context Protocol. Claude, Cursor, Windsurf, and any MCP-compatible agent can call the systems we build as tools.
Anthropic standardA2A
Agent-to-Agent protocol. Our deliverables publish Agent Cards so other agents discover capabilities automatically.
Google standardREST / OpenAPI
Full OpenAPI 3.0 specifications on every deliverable. Humans, dashboards, and agents all use the same endpoints.
OpenAPI 3.0Frequently Asked Questions
Two decades of hands-on delivery experience at tier-1 telecoms and finance. We combine executive advisory with real engineering — we don't just write strategy decks, we also build the systems. Our frameworks are used by top-tier CTOs to move from intuition-based to data-driven AI investment.
Our standard engagement is a 10-week structured program: 2 weeks evaluation & alignment, 2 weeks use case prioritisation, 2 weeks business case development, 2 weeks technical feasibility, and 2 weeks go-to-market planning. Optional extensions cover PoC execution and governance support.
Both — but the reports come with working code attached. A typical prototype engagement delivers a functional MVP, API endpoints, and a dashboard in 4 to 8 weeks. The goal is to validate commercial traction and technical feasibility together, not in sequence.
Yes. Most of our engagements run as joint delivery with client teams. We bring frameworks, architecture patterns, and delivery velocity; your team brings domain knowledge and long-term ownership. This hybrid model is how knowledge transfer actually happens.
Telecom, finance, insurance, energy, and enterprise SaaS. Our team has delivered AI and data engineering projects for tier-1 telecom operators in Europe, LATAM, and North America, as well as banks, insurers, and energy companies. Specific client names are held in confidence; industry references are available on request.
Let's Turn Your Use Case Into a Working System
No generic pitch decks. No AI-washing. Just a conversation about what you're trying to achieve and whether we're the right team to help you get there.