Solutions

Problems we’re built to solve.

Some challenges recur across organizations and industries. These patterns show how we approach each one — the reasoning, the building blocks and the services involved.

These are solution patterns, not case studies. They describe how we approach a class of problem. Every engagement is shaped by its own constraints, and we’re happy to talk through how a pattern would apply to yours.

01/Pattern

Modernize a legacy platform without stopping the business

The challenge: A core system has become slow to change and risky to touch, but the business cannot pause while it is replaced.
Our approach: Map the domain, place a facade in front of the legacy system and migrate capabilities one at a time behind it — with tests that prove behavior is preserved at each step.

Domain mapping
Incremental migration
Contract tests
Observability

02/Pattern

Build security into an existing application estate

The challenge: Security reviews happen late, findings pile up and nobody is sure which risks matter most.
Our approach: Threat-model the critical paths, add automated checks to the pipeline, harden configurations and turn findings into a prioritized, owned remediation plan.

Threat modeling
Pipeline security checks
Hardening baselines
Remediation plan

03/Pattern

Consolidate financial data into one trustworthy view

The challenge: Financial data lives in spreadsheets, bank exports and separate systems, and reconciling it takes days.
Our approach: Model the financial domain explicitly, build validated ingestion from each source, reconcile automatically and present role-appropriate dashboards backed by a full audit trail.

Domain modeling
Validated ingestion
Automated reconciliation
Audit trails

04/Pattern

Take a SaaS product from prototype to platform

The challenge: A product needs to reach real customers quickly — without decisions that force a rewrite at scale.
Our approach: Design tenancy and data isolation up front, ship a focused first release, then add billing, observability and operational tooling as the product proves itself.

Multi-tenant architecture
MVP scoping
Subscription billing
Observability

05/Pattern

Put AI into a business workflow — safely

The challenge: AI could take on real knowledge work, but accuracy, privacy and accountability are genuine concerns.
Our approach: Ground the model in approved sources, evaluate it against realistic cases before launch, keep people in the approval loop where stakes are high and log every recommendation.

Retrieval-augmented generation
Evaluation suites
Human review
Audit logging

Related: AI & Data, Cybersecurity

06/Pattern

Make every release predictable

The challenge: Releases are stressful, regressions reach customers and manual testing cannot keep pace with delivery.
Our approach: Introduce risk-based test automation, wire quality gates into CI/CD and track performance against agreed budgets so each release ships with evidence.

Test automation
CI/CD quality gates
Performance budgets
Release reporting

07/Pattern

Connect systems that do not talk to each other

The challenge: Critical data is copied between systems by hand, creating delays, errors and blind spots.
Our approach: Define clear integration contracts, choose the right pattern — APIs, events or scheduled synchronization — and monitor every integration so failures surface immediately.

API design
Event-driven integration
Data validation
Integration monitoring

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