These are the patterns our team builds in production. Not marketing diagrams. Each one solves a specific business problem we have delivered before.
Most mid-market checkout flows are wired to a single payment provider with no fallback. When that provider has an outage, sales stop. We build an orchestration layer that routes transactions across multiple providers, retries safely, and reconciles cleanly.
A routing engine picks the best provider for each transaction based on amount, payment method and provider health. Every system that needs to know about a payment — finance, CRM, fulfilment — receives one consistent notification, regardless of which provider settled it.
Sales teams live in the CRM. Finance lives in the ERP. When those two systems drift, the business pays for it in lost deals, duplicate invoicing, and angry month-end calls. We build the sync layer that keeps them honest.
The sync watches both systems for changes and processes them in controlled batches. Failures on individual records are queued and retried automatically rather than silently dropped. Conflicts are flagged for review rather than silently overwritten.
Pipelines fail in two places: when volume spikes, and when they hit a memory ceiling on the server they were never sized for. We design data workloads that process in controlled chunks, hold a predictable footprint, and recover from partial failure without reprocessing everything.
One recent implementation processes around 400 000 records per run and finishes in roughly six minutes, staying within a fixed server memory limit throughout. It achieves this by working in small batches and loading reference data once up front rather than hitting the database on every record.
Most AI demos work on clean data under no load. Production AI fails because the responses were never grounded in real data, the outputs were never validated, and there is no record of what the model decided. We build pipelines with accountability built in from the start.
The AI searches your own documents and data before it answers, so responses are grounded in your actual content rather than general model knowledge. Outputs are structured so your systems can act on them directly. A scoring layer checks every response and routes uncertain answers to a person before they reach anyone.
These are the tools our team ships in production. Not a vendor list — technologies that have earned their place across real engagements.
Every engagement ships working software into your environment. The patterns above are the foundation we start from. The build is shaped by what your business actually runs.
Code lives in your Git provider from day one. We work in your repo, your CI, your branch strategy. No hostage code.
Architecture decision records, sequence diagrams for non-obvious flows, and runbooks for the failure modes that matter on call.
Integration tests against the surfaces that actually break. Not coverage theatre. Targeted at the brittle joins between systems.
Live handover with your engineers. We answer the why questions, not just the what. Your team owns the code after delivery.
