Services
Architecture work products.
Every engagement produces documents that an engineering team can build from and a non-technical owner can still follow. These are the work products we deliver.
Target platform architecture
A target architecture that consolidates per project builds onto a common, reusable backend and delivery platform. We define the shared services, the separation between tenants or clients, and the configuration boundaries, so that new engagements are delivered from a common foundation instead of being rebuilt from scratch each time.
API and integration architecture
A unified integration layer governing CRM connectors, spreadsheet integrations, inbound and outbound webhooks, and payment integrations. Includes API contract standards, versioning, idempotency handling, retry and backoff policy, and failure isolation so that one third-party provider going down does not take the platform with it.
Backend services architecture
Service decomposition and boundaries, including how new services in Kotlin or Java coexist with backends you already run in Python or Node. Covers deployment topology, environment strategy, and cloud resource layout.
Event and job processing architecture
An event driven and scheduled job architecture for asynchronous workloads. Where a message broker is involved, we deliver a written comparison of Apache Kafka and RabbitMQ evaluated against your specific load profile, delivery guarantees, ordering requirements, and operational overhead, followed by a recommendation and a queue, topic, and retry design. Streaming pipelines are designed with data quality controls built in, not bolted on.
Data architecture
Data layer design across PostgreSQL and MongoDB: schema design, indexing strategy, and caching policy in Redis, with query optimization for high-load workloads. Where reporting and product analytics are in scope, we define the ETL approach that feeds them.
Authentication, authorization, and access control
A single authentication and authorization architecture spanning your products and delivered systems: identity model, token strategy, role and permission model, service to service authentication, secrets handling, and database access controls. Over-privileged access paths are identified and designed out.
AI integration architecture
The architecture supporting AI features and AI assisted workflow automation: model invocation boundaries, prompt and context handling, on device processing against server side inference, cost and rate limit controls, evaluation hooks, and data handling safeguards.
Implementation plan and technical review
A written, sequenced implementation plan covering migration phasing, a technical risk register, and capacity planning, together with a security review of the proposed architecture. This is the document that turns the design into scheduled work.
Also available
Implementation and technical direction
Architecture that nobody implements is an expensive document. Where a client wants it, we stay past the design.
Leading implementation
Building the services the architecture calls for, in Kotlin and Java, applying asynchronous patterns for scalable workloads.
Design and code review
Review of implementation work against the agreed architecture, with written findings rather than verbal approval.
Technical direction
Capacity planning, technical risk assessment, and security review as the systems and the team grow.
Not sure which of these you need?
That is normal, and it is what the discovery phase is for. Describe the systems and the symptoms, and we will scope it.