Emerging technologies
Positioning and strategy for technologies ahead of their adoption curve — identifying value before market adoption.
Capability · Technology Strategy
Technology as an asset.
This is where design and engineering meet long-term business goals.
01 Capability
Twenty-five years designing technology to capture value. We build strategies grounded in engineering, focused on what compounds rather than depreciates. What to build, where to pivot, when to double down.
02 Domains
Product roadmaps
Where the product is going, what the technology needs to excel, and roadmaps that compound value across longer timeframes.
Technology asset strategies
Technology as an asset — what to build, what to buy, what to partner on. Portfolio-level decisions shaped by long-term goals.
AI adoption
Strategic roadmaps for enterprise AI adoption, rooted in measurable gains rather than vendor narratives.
R&D strategies
Research planning for technologies that deepen the value proposition. Roadmaps to transition from research to commercial IP.
Partnership roadmaps
Joint venture design, shared-IP structures, equity engagements — how value gets captured across organisational boundaries.
03 Our position
Technology can be an asset, unlocking new opportunities and delivering growth — or it can be a liability, locking a business into processes too early or into tools that become inflexible exactly when agility is needed. Few software firms will address this, delivering to the brief and moving on, without long-term investment in the business outcomes the technology is meant to produce.
This is where we challenge the model. Future value in technology comes from two directions: from inside the business's own industry or domain, and from the tech industry itself — the right tools, built on the right primitives, at the right time. Reading both is how durable value gets identified. Structuring for both is how that value gets captured.
In an industry that requires concerted forward planning to keep the advantage, our depth of hands-on and strategic understanding is our differentiator.
Forward Planning
04 In practice
Where this work shows up.
Full-lifecycle SaaS platform
Full-lifecycle engagement for a multi-national SaaS in property management. From technology strategy through to market launch, with substantive R&D required for the unique technology stack underneath.
Apple Silicon Vector Database
A bet on Apple Silicon as a strategic vertical. Existing vector databases leave on-device GPUs idle; this puts them in developers' hands. With vector retrieval rising, on-device AI ascending, and Apple's silicon advantage compounding, this is positioned to become a backbone of Apple's AI strategy.
Collaboration as the primitive
Ahead of its market. mgraph is a delta propagation engine that synchronises complex data types — tensors, vectors, streams, graphs, diffs — across server, app, and browser, turning each into an edge node. Positioned to power CDN 2.0 for structured data coordination.
Composable on-device intelligence
On-device intelligence pipelines composed as DAG graphs of primitives — inference, vector search, index, traverse, rank, train. msearch rides the converging trends of on-device AI demand, distributed systems, agentic RAG, and locally-trained models. The intent: composability at the developer and knowledge worker level.
Works with
Other engagement models
01
Strategic Advice
The primary engagement model for strategy work. Paid, scoped, opinionated.
Read more →02Partnerships & Equity
When the strategic call is to back the bet alongside you, not just to advise on it.
Read more →03Engineering & Development
When the strategic answer is "the build is the strategy" and we stay through delivery.
Read more →Capabilities
01
Architecture & Infrastructure
The technical artefact a strategy is downstream of, or an investor is reviewing.
Read more →02AI, ML & Neural Architectures
Where most strategy questions land in 2026 — adoption, IP, runtime decisions.
Read more →03Software Development
When the strategy is simply the software.
Read more →Contact
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