Ignition to Impact
Most data work stops halfway: platforms that cannot answer the question or cope with the load, models that never reach production, knowledge that changes nothing. We work the whole loop, and keep it turning.
- framing the question
- building the data platform
- forming the team
- extracting intelligence
- determining the impact
- crafting the narrative
- making change
Global motorsports · Olympic broadcast · Investment banking · Trading since 2009
Three stages, and a return path.
Act on it
Knowing is only half the battle - we effect change. We work through the real-world impacts, craft the compelling narratives that change minds and help you reshape your business processes and culture.
the questions change as you grow
Most firms only work one arc of it.
Data engineering firms build the platform and hand it over. Analytics firms arrive after the platform is set and work with what they find. That leaves you owning the gaps between them, and the job of pulling it all together. We all know where this leads:
- A pipeline that captures everything except the field the model needed.
- A platform that meets your immediate needs but cannot grow with you, failing slowly from day one.
- An expensive transformation layer that exists only because the data was stored in the wrong shape.
- A model too slow or too costly to serve inside the product.
- A set of recommendations on a shared drive that everyone agreed with and nobody owns.
Palefire can build the loop from scratch, shore up the parts of yours that are weakest, or take on a scoped piece with a clear eye on the big picture.
Production-grade, at scale, under pressure.
The work spans regulated finance, live broadcast, elite sport, and global education. Always with real stakes, always in production.
- Experience
- 25+
- Clients
- 40+
- Scale
- 10+ PB
- Latency
- <10ms
Years designing and operating production systems
Startups and scale-ups engaged since 2006
Media archive migrated for a global sports organisation
Timing data captured and distributed live at a world championship
The team is part of the platform.
A platform is not only hardware and software. It is the people, the processes and the culture that keep it alive. So the question is never just what gets built, it is who is going to run it, and whether they still can in a year.
Assembled in weeks
People
A broad technical network and long recruiter relationships mean a team can be in place in weeks, against the three to six months a senior hire takes in search, fees and risk. Pre-vetted, not pre-paid: nobody sits idle on your invoice.
Written down, not remembered
Processes
Runbooks, review, on-call, the release rhythm, and increasingly the agents running parts of it. The unglamorous machinery that decides whether the platform still works in a year, and whether anyone can operate it without the person who built it.
Built on purpose
Culture
How a team decides what good looks like, and whether that holds when the deadline is real and immovable. It is the part nobody writes into a statement of work, and the part that determines whether the other two survive contact with pressure.
Hardware and software are the easy half to buy. For a company counting runway, every month spent searching for a senior engineer is a month of burn against a roadmap that has not moved, and a platform nobody has learned to run yet.
What we are thinking about.
Method notes and arguments from the work, written up while they are still fresh enough to be useful.
- Essay3 min read
Symbolic, testable tools for neural agents: a small neurosymbolic example
Frank Coyle argues that neural agents need to be tethered to symbolic, testable tools. The platform behind the Inchcape collision-parts engagement is a small, concrete instance of exactly that, long before an agent is in the loop.
Read article - Case study4 min read
Rails for data science: the platform beneath a forecasting engine
A shared library, a model contract and a Features API let a distributed team evaluate many forecasting models safely, and turned feature search into something you can automate. Notes from the Inchcape collision-parts engagement.
Read article - Case study3 min read
Learning platforms for Inkstone
How we built and evolved a custom learning platform family for an Auckland EdTech business, from legacy Drupal stack to a multi-tenant, enterprise-grade system serving Japan's top professional firms.
Read article
Have a hard data problem worth solving properly?
Palefire takes a small number of engagements each quarter. If you need a partner to design a platform, make sense of the data already in it, or make an AI system trustworthy enough to ship, start with an email.
- rdd@palefire.io
- Studio
- London · Remote worldwide