AI / ML Solutions
From a validated use case to a model running in production — with evaluation, guardrails, and a cost ceiling you agreed to up front.
- RAG & retrieval pipelines
- Model evaluation harnesses
- MLOps: training → serving → monitoring
AI · Software · Cloud · Operations
BinaryRise is a boutique technology consultancy. We design, build, and operate AI and data systems, custom software, and the cloud infrastructure underneath them — with senior engineers on every engagement, start to finish.
No sales deck. You talk to the engineer who'd do the work.
What we do
Most problems cross all four. We staff them that way — not with four vendors and a coordination tax.
From a validated use case to a model running in production — with evaluation, guardrails, and a cost ceiling you agreed to up front.
Custom applications and integrations, built to be handed over: documented, tested, and yours.
Architecture and migration on AWS, Azure, or GCP — infrastructure as code from day one, no click-ops.
The unglamorous layer that decides whether everything above it stays up. Monitored, patched, and documented.
How we engage
Fixed-scope discovery. Your repositories and cloud accounts. No lock-in clauses.
A prioritised use-case shortlist, a data-readiness assessment, and one working prototype.
A modelled warehouse, automated pipelines, and dashboards your team can extend without us.
A documented target architecture, an IaC-managed environment, and a migration runbook.
A paid discovery session. We map the system, the constraints, and the failure modes.
You leave with: a written problem statement and a scoped proposal — yours to keep, even if you stop here.Target architecture, tradeoffs written down, and the decisions we'd defend in six months.
You leave with: an architecture doc and an ADR log.Two-week increments. Working software at the end of each. Your repo, your cloud account, our commits.
You leave with: reviewable code from week two.Monitoring, runbooks, and a handover your team can actually use — or ongoing support if you'd rather we kept it.
You leave with: runbooks and a handover session.Our toolkit
We're deliberately not tied to one vendor. The stack follows the problem — and we'll tell you when the boring option is the right one.
Cloud
Data & AI
Languages & frameworks
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Engineering notes
Architecture decisions, tradeoffs, and things that broke — written by the people who build.
All articles
Retrieval quality and answer quality fail in different ways, and a single score hides both. Measure the two stages separately, on a set you wrote by hand.

Account structure, naming, state layout, network topology and identity. Everything else in a landing zone is reversible; these five are not, so decide them first.

The projects that survive contact with production are the ones whose failure mode is obvious. Pick a problem where being wrong is cheap and visible.
Taking on new projects for [quarter]
Start a conversation
A short description is enough to start. If we're not the right fit, we'll say so and point you somewhere better.