Already have a developer or agency? We sit on your side of the table.
A lot of non-technical founders reach us here: you've hired someone to build your product, and you have no way to independently tell if the work is good, the pace is normal, or the decisions being made are the right ones. That's what this is for.
Start with a short call — we listen to what's going on and scope what a proper review would involve.
You get a priced, written report — the depth and cost depend on the complexity of what's being reviewed.
We work for you, not your vendor — so the read you get isn't the one they'd rather you hear.
We build data systems from scratch — and turn messy data into structure.
Wherever the raw data lives — documents, databases, disconnected tools, years of inconsistent records — we design and build the system that structures it, automates around it, and holds up as it grows. Build it from scratch, or bridge the gaps in what already exists.
Two other ways to work with us
Beyond sitting in as your technical counsel, we also take on the work directly — either from a blank slate or fixing a specific part of a system that already exists.
Products & systems, built from scratch
No existing system to extend, or the existing one needs to be rebuilt. We design and build the data product or infrastructure end to end and hand over something the team can run.
- New data platforms and internal tools
- End-to-end pipelines and automation
- Infrastructure for a product that doesn't exist yet
Consulting to bridge specific gaps
A system already exists, but something in it isn't working — data quality, a pipeline that keeps breaking, a process that hasn't been automated yet. We find the gap and fix that part.
- Diagnosing pipeline or data-quality issues
- Targeted fixes to an existing system
- Short, scoped engagements around one problem
Built on years of large-scale, messy data
Years spent building the data systems behind large-scale transactional and document-heavy platforms — government-scale records, inconsistent third-party sources, and datasets that arrived hard to structure. That depth is domain-agnostic: the same system-building applies to any dataset that starts out messy and needs to become reliable.
NoSQLdatabase expertise across every build
Built by people who've run this at scale
Not a framework applied generically — a way of working shaped by years of building systems that had to survive real, messy data.
Understand the data as it actually is
Before proposing a fix, we look at the real records — inconsistencies, edge cases, exceptions that break naive assumptions.
Design for the messy case, not the clean demo
Pipelines and extraction logic are built to survive the data you actually have — not a tidy sample.
Automate what should never be manual again
Once a process is understood, we find what can be automated safely — using AI/LLM tooling where it earns its place.
Hand over something the team can run
Documented, maintainable systems — not a black box that only works while we're in the room.
The work, in detail
The common thread is structure and clarity: taking something ungoverned, opaque, or half-built and making it something a team — technical or not — can act on.
Working on a data-heavy problem? Let's talk.
Grab a 15-minute slot — enough time to describe what you're working on and figure out if this is a fit, no prep needed.
- 15 minutes, no obligation
- Bring a rough idea — details can wait
- Pick whatever slot works for you