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Software · AI · Cloud · Data

The problem defines the engineering team.

SDK brings together the specialists a system actually requires, coordinates their work and remains accountable for delivery quality. Start with one technical decision or give us a defined workstream to own.

Discuss a project →Find your starting point
  • Problem-led team composition
  • Independent specialists
  • SDK-led quality control
  • Client-owned systems

Start with the pressure on the system.

A useful engagement starts with the constraint, not a catalogue of technologies.

  1. 01ModernizeReduce the risk and cost of changing software that can no longer keep accumulating patches.
  2. 02BuildDesign and deliver backend platforms, integrations and product systems around a clear operating need.
  3. 03AutomatePut AI into a real workflow with the data, evaluation and operational controls it needs.
  4. 04StabilizeFind the causes behind reliability, deployment, performance or data-flow problems.
  5. 05DiagnoseTurn an unclear technical situation into evidence, options and a defensible next decision.

Capabilities

Engineering depth, organized around the decision in front of you.

Each capability can stand alone or combine with others when the system crosses boundaries.

01 / MODERNIZATION

Change an aging system without losing what still works.

The system matters to the business, but upgrades are risky, delivery is slowing down or too much knowledge sits in undocumented behavior.

What we examine

  • Dependencies, runtime constraints and unsupported components
  • Data flows, integrations and hidden operational coupling
  • Change risk, test coverage and migration boundaries

What we can deliver

  • Current-state assessment and prioritized modernization plan
  • Framework, runtime or service migration
  • Incremental replacement with controlled cutover

Relevant systems

PHP · Laravel · Symfony · Java · Spring Boot · Node.js · PostgreSQL

Useful first move

Map what the system does today, where change is dangerous and which boundary can move first.

02 / PLATFORMS

Build the parts of the product that carry the business rules.

A product needs APIs, integrations, authorization, asynchronous work or realtime behavior that must remain understandable as requirements change.

What we examine

  • Domain boundaries, users and access rules
  • Integration contracts, failure modes and data ownership
  • Operational volume, latency and consistency requirements

What we can deliver

  • Backend services, APIs and integration layers
  • Authentication, authorization and tenant isolation
  • Queues, events and realtime application flows

Relevant systems

Java · Spring Boot · Node.js · PHP · PostgreSQL · Redis · Valkey

Useful first move

Define the business boundary, the data it owns and the failure conditions the design must tolerate.

03 / AI AUTOMATION

Move AI from a convincing demo into an accountable workflow.

A manual process is expensive or slow, but an AI feature will only be useful if its inputs, outputs, evaluation and fallback behavior are controlled.

What we examine

  • Workflow decisions that require a model and those that do not
  • Source data, permissions and retrieval quality
  • Evaluation criteria, human review and failure handling

What we can deliver

  • LLM integrations, agents and workflow automation
  • Retrieval and grounded response systems
  • Evaluation, observability and review controls

Relevant systems

LLM · RAG · APIs · PostgreSQL · Elasticsearch · Python · Node.js

Useful first move

Choose one workflow, define an acceptable result and measure the current human process before automating it.

04 / PRODUCTION SYSTEMS

Make production behavior visible before changing capacity.

Deployments are fragile, incidents are hard to explain, infrastructure costs are unclear or the system is approaching an operational limit.

What we examine

  • Deployment path, environments and recovery procedures
  • Logs, metrics, traces and incident evidence
  • Resource constraints, bottlenecks and scaling assumptions

What we can deliver

  • Deployment architecture and CI/CD workflows
  • Observability, alerting and operational runbooks
  • Cloud, container and orchestration improvements

Relevant systems

AWS · GCP · Azure · Kubernetes · Helm · CI/CD · Redis

Useful first move

Establish what the system is doing under real load and how the team currently detects and recovers from failure.

05 / DATA & INTERFACES

Connect data, operations and the people using the system.

The product needs a dependable data path and an interface that makes complex operational work easier to understand and complete.

What we examine

  • Data ownership, lifecycle, search and access patterns
  • User tasks, decision points and error recovery
  • Server and browser boundaries that affect performance

What we can deliver

  • Data models, search, cache and ingestion flows
  • Operational web interfaces and internal tooling
  • Accessible, responsive application experiences

Relevant systems

PostgreSQL · MongoDB · Elasticsearch · React · Vue · Nuxt · TypeScript

Useful first move

Follow one critical user task from source data to final decision and identify where context is lost.

Ways to engage

Match the commitment to what is already known.

An uncertain system needs evidence before a responsible implementation commitment. A defined outcome can move directly into a focused workstream.

Best for

Technical assessment

A consequential decision where the current state, risk or implementation path is unclear.

Engineering workstream

A defined technical outcome that needs a composed team and clear delivery ownership.

Technical partnership

A system that needs staged modernization or continued ownership of a technical workstream.

Primary output

Technical assessment

Evidence, options, risks and a prioritized recommendation the client can use with or without SDK.

Engineering workstream

Working changes, reviewed decisions, deployment evidence and documentation for the agreed scope.

Technical partnership

A maintained roadmap, incremental delivery and an operating record of decisions, risks and progress.

Commitment

Technical assessment

A bounded investigation with agreed access, questions and deliverables.

Engineering workstream

A focused delivery period with visible checkpoints and acceptance criteria.

Technical partnership

A continuing engagement reviewed against an agreed workstream and priorities.

The SDK model

Specialists selected for the system. One company accountable to the client.

SDK works with independent engineering specialists. We compose the team around the problem, coordinate the work and set the quality framework for the engagement. The client does not need to recruit, align and manage a collection of unrelated contributors.

  1. Define the need

    01

    Clarify the system, constraints, decisions and outcome before deciding who should do the work.

  2. Compose the team

    02

    Select the disciplines and experience relevant to the engagement instead of forcing it into a fixed bench.

  3. Control quality

    03

    Use visible decisions, reviews, acceptance criteria and operational evidence throughout delivery.

  4. Transfer ownership

    04

    Keep code, infrastructure, documentation and operating knowledge in the client’s control.

Bring us the constraint

You do not need to arrive with a finished specification.

Describe the system, the pressure on it and the decision you need to make. We will start by determining whether SDK is a useful fit.

Discuss the problem →