Services

What do you need to move forward?

You may need software delivered, a business process improved or help for an existing engineering team. Explore the three offers below.

You need software delivered

Build, improve and connect your software

Build →

You have a business task or process to improve

AI agents and workflows for everyday work

AI Agents & Workflows →

You already have an engineering team

Help your team deliver with AI

AI Engineering →

Build

You need software delivered

Build, improve and connect your software

From a simple website or mobile app to APIs, web services and complex business systems. We connect requirements, UX, architecture, implementation and integration around what your users and business need to do.

Discuss what you need to buildExplore earlier software and integration experience

Scope

  • Websites, mobile applications and digital platforms
  • Modular architecture, frontend, backend, APIs and web services
  • Integration, modernisation and cloud capacity suited to your needs
  • Automated unit, integration and regression tests, AI-assisted QA and human acceptance review within the agreed scope
  • Release, handover and separately scoped maintenance or improvement

What you receive

An agreed release scope and acceptance criteria, relevant UX and architecture, reviewed software and a defined handover. Automated tests, AI-assisted test work and independent AI review support human acceptance decisions. Agents can execute approved deployment workflows; human operators remain responsible for release. Continuing operation and improvement are agreed with you.

Proof: Tribeca Festival Lisboa — website & content platform

After launch: Keep accepted software and workflows useful through agreed monitoring, maintenance, exception handling and improvements. CMS, social and business-process tasks can be included where their inputs, permitted actions and human decisions are defined. Agreed continuation

AI Agents & Workflows

You have a business task or process to improve

AI agents and workflows for everyday work

Ask an AI agent to update a website page, prepare social content, organise documents or move information between systems. We build the workflow around your existing tools and agree what it can change, with human approval before publication. For small and medium-sized businesses, one useful task is a practical start; a pilot helps when the benefit needs evaluation.

Explore one task for AI

Scope

  • Small business tasks and connected process workflows
  • Website updates through agents or your CMS, and social-content preparation with review before publication
  • Document, knowledge and information-handling tasks
  • System integration, evaluation and operational responsibilities
  • Opportunities identified from authorised workflow evidence and evaluated before changes

What you receive

A mapped task, a baseline, a bounded pilot or implementation and agreed measures for output quality, human effort, exceptions and cost. The result supports a decision to stop, adapt or extend. Access, publication and continuing operation are scoped explicitly.

Proof: AI Editorial Desk (running for live publications; Devmojos website integration planned) and Brief to Shortlist (live with test agencies; not a production service)

AI Engineering

You already have an engineering team

Help your team deliver with AI

Help your team build, test and improve software with AI. We assess your delivery process, introduce a focused change and measure its effect on quality, delivery time and cost. Architecture, independent review and human release decisions guide the work.

Discuss your team's delivery processExplore earlier engineering experience

Scope

  • Specifications, context, modular boundaries and task ownership
  • Agent coordination, independent review and automated/regression tests
  • Model and tool evaluation against the task and operating constraints
  • Human acceptance decisions and approved deployment workflows

What you receive

A process assessment, a scoped adoption experiment, practical review and handoff rules, and evidence against agreed delivery measures. Your team keeps responsibility for the system and for deciding which changes to retain.

Proof: Current internal agentic harness and Devbus practice

How a project starts

Three steps before any build

Tell us what you want to build or improve and how the work happens today. We’ll discuss a project scope, a useful AI task or an assessment with your engineering team. A pilot can help where the benefit needs testing. Ongoing operation is agreed separately.

  1. Write to usDescribe the software, business task or engineering process you want to improve.
  2. We establish fitA first conversation about users, systems, constraints and what evidence would make the result useful.
  3. Agree the scopeA project scope, a one-task pilot or a team assessment, with human decisions explicit.

Questions we are usually asked

Who makes the decisions when AI agents do the implementation?
Business priorities, UX, architecture and acceptance guide the work. AI agents implement defined tasks and can execute approved operational steps. Human decisions remain explicit from discovery to release and continuing improvement.
What do we actually receive?
Build: An agreed release scope and acceptance criteria, relevant UX and architecture, reviewed software and a defined handover. Automated tests, AI-assisted test work and independent AI review support human acceptance decisions. Agents can execute approved deployment workflows; human operators remain responsible for release. Continuing operation and improvement are agreed with you. AI Agents & Workflows: A mapped task, a baseline, a bounded pilot or implementation and agreed measures for output quality, human effort, exceptions and cost. The result supports a decision to stop, adapt or extend. Access, publication and continuing operation are scoped explicitly. AI Engineering: A process assessment, a scoped adoption experiment, practical review and handoff rules, and evidence against agreed delivery measures. Your team keeps responsibility for the system and for deciding which changes to retain.
Can you work with our existing engineering team?
Help your team build, test and improve software with AI. We assess your delivery process, introduce a focused change and measure its effect on quality, delivery time and cost. Architecture, independent review and human release decisions guide the work.
How small can an AI workflow start?
Ask an AI agent to update a website page, prepare social content, organise documents or move information between systems. We build the workflow around your existing tools and agree what it can change, with human approval before publication. For small and medium-sized businesses, one useful task is a practical start; a pilot helps when the benefit needs evaluation.
What happens after launch?
Keep accepted software and workflows useful through agreed monitoring, maintenance, exception handling and improvements. CMS, social and business-process tasks can be included where their inputs, permitted actions and human decisions are defined. Availability, responsibilities and commercial terms are agreed for the continuing scope.
Is AI-written content labelled?
Our editorial policy requires human approval before publication on the Devmojos website. News analysis credits and links to its sources. Articles identify AI assistance or authorship.

Technology chosen for your system. AI chosen for the job.

Your systems, user needs, expected load and operating constraints guide the technology choice. We use clear boundaries, modular architecture and appropriate AI tools to support implementation, evaluation and future changes.

Current AI practice

  • Claude logoClaudeAI assistant & models
  • OpenAI Codex logoCodexAI coding agent
  • Grok logoGrokAI assistant & models
  • Qwen logoQwenModels & coding tools
  • Gemini logoGeminiAI models
  • vLLM logovLLMModel serving
  • LiteLLM logoLiteLLMModel routing & gateway

AI assistants & coding tools

Claude CodeCodexQwen CodeGrok Build

Coding agents used within defined responsibilities, shared context and independent review. Tool choice follows the task and delivery constraints.

Model ecosystems

OpenAI GPT modelsClaudeGrokQwenGemini

Model choice follows the task, integration needs and evaluation criteria. We compare hosted services with self-managed options where available, against your data, control and operating requirements.

Model serving & routing

vLLMLiteLLM

Serve models with vLLM or connect providers through LiteLLM where the project needs them. Hosting, API compatibility, capacity and maintenance requirements guide the deployment.

Agent workflows & quality

Agentic harnessDevbusRoles skills & playbooksRecorded handoffsPlaywrightNode.js testsIndependent model review

Task-specific model serving and evaluation, recorded handoffs and controlled work. The current harness and Devbus support our engineering practice. Playwright checks, Node.js tests and independent model review provide evidence for human acceptance decisions.

Integration

REST/OpenAPIMQTT/KafkaSalesforce/SAP

Connect AI workflows to existing APIs, event streams and business systems through interfaces agreed for the project. Integration choices follow your current systems and the work people need to do.

Languages & runtimes

JavaScript / TypeScriptPythonJavaNode.jsCC++DartGoKotlinObjective-CPHPScalaSwift

Choose languages and runtimes around your application, existing codebase and the skills needed to maintain it.

Frameworks

ReactAngularVueFlutterFastAPIFlaskNestJSSpring Boot

Selected technologies from documented delivery experience. We assess the right fit for the project and your existing environment rather than prescribe one framework.

Cloud platforms

AWSAzureGoogle Cloud

Select cloud services around existing infrastructure, hosting requirements and operating responsibilities.

Delivery & operations

CI/CDDockerKubernetesTerraformCloudFormationDatadogGrafanaHelmSwarmAutomated & regression testsMonitoring

Infrastructure, capacity assumptions, tests and ongoing operation are designed around the agreed scope. Automated and regression tests, AI-assisted QA and independent review support human acceptance decisions. AI agents can execute approved deployment workflows; human operators remain responsible for releases.

Review & evaluation

  • Jev / TypeSafe logoJev / TypeSafeTyped judgments
  • Playwright logoPlaywrightBrowser automation

Typed judgments and browser automation provide additional evidence for review. We choose checks around the task and acceptance criteria; people remain responsible for decisions and release.

An ecosystem to shape around your project

These are options we consider and evaluate around your knowledge, workflows and operating constraints. Selection depends on the task, source quality, integration needs, evaluation criteria and hosting choices.

Knowledge & retrieval

  • Obsidian logoObsidianKnowledge workspace
  • RAGRetrieval method
  • LlamaIndex logoLlamaIndexRetrieval workflows
  • Qdrant logoQdrantVector search
  • pgvectorPostgreSQL vector search

Explore ways to retrieve relevant material from your documents and notes, keeping source context available for review. RAG is a retrieval method; workspace, indexing and search choices depend on how your knowledge is organised and maintained.

Workflows, evaluation & model access

  • LangGraph logoLangGraphAgent workflows
  • n8n logon8nWorkflow automation
  • Langfuse logoLangfuseLLM observability & evaluation
  • Ollama logoOllamaLocal model runtime
  • MCP logoMCPTool connectivity protocol

Consider how AI steps connect to existing business systems, where people review the work and how results are evaluated. Workflow tooling, model access and hosting are selected around your data, control and operating needs.

Selected delivery experience and current AI engineering practice. We agree the exact project stack and operating responsibilities during scoping.