We help organisations identify internal operational pain points and strategically apply AI to resolve them.
#EnterpriseAI #Efficiency #MultiAgent #Bespoke #ROI
Every business leader knows their company should use AI — to become AI-native. Most have experimented with it; and if they haven’t, their employees certainly have. Modern business has evolved, and to remain a leader you must accelerate both delivery speed and output quality.
Yet studies show over 80% of enterprise AI projects deliver no return on investment. Our approach is based on our own practical experience. It prioritises designing and implementing solutions to unblock your specific operational bottlenecks — over model selection — and driving employee engagement.
We partner with you to re-engineer core workflows, navigate organisational friction, and deploy bespoke, custom-built multi-agent AI systems with measurable metrics designed to drive meaningful
business results. This includes forward-deployed engineers (FDE) working inside your organisation to deploy vertically-integrated AI.
10+ yrs — Shipping production software
98% — Of our own code now written by AI
2mo→3wk — Sales cycle cut with ChatStack
Stage 01 — Enterprise Efficiency
Identifying corporate pain points and friction to leverage AI solutions.
Our process begins with listening. By conducting structured discovery interviews with your primary stakeholders, we
pinpoint the specific workflows where AI generates tangile ROI. We prioritise these opportunities based on actual
business value and the reduction of manual cycle times — rather than focusing on technological trends.
“We don't start with the model - we start with the bottleneck. A two week opportunity assesment surfaces where AI delivers real ROI across operations, support, and back-office.”
Stage 02 — Strategic Planning & Adoption Barriers
Identifying and navigating enterprise AI adoption obstacles.
Success in AI initiatives is typically determined by adoption rather than technical deployment - we’ve seen it ourselves, going from writing no code to over 98% AI-assisted in less than a year. The adoption curve is jagged - different teams and individuals adopt at different speeds and in different ways. Challenges often stem from trust, autonomy, and misaligned incentives rather than the technology itself.
We give leadership an unfiltered analysis of data ownership, cultural, regulatory, and functional friction points at the outset - ensuring your organisation has the governance framework, policy structures, and comprehensive audit trails needed for legal and security clearance before any capital is committed.
“We treat barriers as first-class workstreams in every engagement so the roadmap matches what your teams can absorb.”
Stage 03 — Measuring What Matters
Quantifying performance and connectivity.
We bridge the gap between AI strategy and the platforms your teams use every day, giving leadership real-time visibility into operational bottlenecks and adoption friction. We design andbuild custom solutions based on your own technology stack, workflows and operational challenges. By integrating with core but disparate enterprise tools — including GitHub,Slack, Google Workspace, Jira, Figma, Cursor, and Claude - we let you analyse a unified view of existing KPIs or develop bespoke dashboards that monitor progress across your entire digital ecosystem. We also understand your data is confidential and valuable, so our solutions are built on your own infrastructure, often with forward-deployed engineers.
Tools: GitHub · Slack · Google Workspace · Jira · Figma · Cursor · Claude
Proven in Practice : For one client we built a custom dashboard that pulls live data from Jira, Github, Cursor, Slack and Figma to track team productivity, AI spending, error rates and project health. Using bespoke data visualisation, leadership can can see exactly where AI is being adopted - and where it is quietly being avoided. Gamefication elements such as leaderboards, streaks and awards encourage wider engagement across the enterprise. A live product demo of this system is reserved for private consultation.
Stage 04 — Custom Solution Development
Forging customised AI interventions to dismantle operational constraints.
When off-the-shelf tools fall short, we build bespoke, multi-agent AI interventions designed to dismantle your specific operational constraints. By bridging disconnected departments, we re-engineer complex, multi-stage workflows into automated systems — converting raw structured and unstructured data into a tangible strategic asset
for your organisation.
How we work: Process Re-Engineering Around AI — We Eat Our Own Cooking
Our expertise isn’t theoretical; it’s forged from the complete AI-first re-engineering of our own software development operations. As frontier models drastically accelerated our delivery speeds, our traditional pipeline failed to keep pace. The operational friction shifted from execution to the scoping, quoting, and estimation phases — which became critical bottlenecks preventing us from securing projects at the speed of our new development capacity.
A comprehensive audit of our project lifecycle, from initial lead to long-term retainer, revealed a vital truth: AI’s primary value lies in disciplined, AI-assisted planning and precise requirements rather than mere speed of execution. Consequently, our cross-functional teams — PMs, engineers, designers, and the CTO — now dedicate several days to rigorous collaborative planning before any development begins: answering clarifying questions, removing ambiguity, and revising plans. By investing in context and structure up front, we eliminate the instability of “vibe coding” through strict rules and total system observability. It also means that, once the plan is agreed, we can unleash AI coding agents across long-horizon tasks. We apply this same high-level planning rigour to optimise your enterprise workflows.
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Case Study Spotlight: Shortening Sales Cycles from 2 Months to 3 Weeks with ChatStack
For one client, we identified that the sales pipeline — not delivery — was the core business bottleneck. We built a custom multi-agent AI workflow to solve it. We named it ChatStack.
Defining the Anchor: ChatStack functions as a “Cursor for Requirements,” closing the gap between engineering and product teams. Leveraging ten years of software delivery expertise, our system of over 20 specialised AI agents enables teams to produce technical, structured requirements, the recommended stack, and a detailed cost estimate — without writing code, in a single session.
Actionable Output: The platform delivers comprehensive PRDs in AI-ready formats like CSV or JSON, alongside instantaneous fixed-price estimates that integrate seamlessly with MCP-aware IDEs such as Claude Code and Cursor.
The Necessary Trade-Off: Achieving peak precision requires intentional process. ChatStack optimises for both speed and granular detail through focused 10-to-20 minute sessions, ensuring data is organised so AI can decompose requirements into dependable, manageable work units.
The New Paradigm: As the cost of execution drops, the premium on high-level strategy rises. ChatStack represents the fundamental re-engineering of the thinking process.
2mo→3wk sales lead-to-conversion timeline · 20+ agents specialised AI agents in the workflow · 10–20 min per focused requirements session · CSV / JSON AI-ready PRD outputs for MCP IDEs
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