AI-assisted software engineering
Apply hands-on expertise in Codex and Claude Code across discovery, architecture, implementation, testing, debugging, documentation, and code review—with experienced engineers accountable for every outcome.
Applied AI
AI that gets useful work done.
We combine AI with solid software engineering to help teams understand complex information, automate repetitive work, improve existing systems, and move from an idea to dependable production software.
AIEngineering
Knowledge
Workflows
Software
People
Our point of view
The model is only one part of the solution.
Useful AI needs the right context, reliable integrations, clear permissions, measurable quality, and an experience people can trust. We approach AI as an engineering capability—not a disconnected demo—and fit it into the systems and processes your organization already depends on.
What we do
Practical capabilities across the software lifecycle
We use AI where it creates real leverage, while keeping critical decisions visible and reviewable.
Legacy understanding & modernization
Map unfamiliar codebases, trace dependencies, explain business logic, identify risks, and plan incremental modernization for established .NET, Java, web, and data systems.
Knowledge assistants
Create grounded assistants that help people find and understand information across approved policies, manuals, project records, support material, and organizational content.
Document & data workflows
Extract, classify, summarize, compare, and transform information from documents, spreadsheets, forms, and operational data—with validation where accuracy matters.
Workflow agents & automation
Connect AI to APIs and business rules to prepare work, route requests, generate structured outputs, monitor defined conditions, and support multi-step operational processes.
Content, quality & accessibility review
Use AI to improve clarity, consistency, metadata, usability, test coverage, and accessibility—supported by deterministic checks and expert review.
Where it helps
Start with a high-value workflow
Developer enablement & training
Train developers to use Codex and Claude Code effectively: giving tools the right context, planning changes, generating and testing code, reviewing output critically, and applying secure engineering standards to produce high-quality, maintainable, future-ready software.
Operations teams
Request triage, information extraction, guided workflows, recurring reporting, and exception-focused review.
Knowledge-heavy organizations
Search and question answering across governed content, with sources and access boundaries preserved.
Product teams
AI features embedded into existing web, mobile, enterprise, laboratory, analytics, and public-facing platforms.
Responsible by design
Control is part of the architecture.
We shape the safeguards around the risk of the workflow, rather than treating every AI use case the same.
- Grounded outputsUse approved sources and show evidence where appropriate.
- Human oversightKeep consequential decisions with authorized people.
- Data boundariesApply access controls, minimization, and environment-aware handling.
- EvaluationTest quality, failure modes, security, cost, and performance before scaling.
How we engage
From useful idea to working capability
- 01
Discover
Choose a workflow with clear users, inputs, risks, and business value.
- 02
Prove
Build a focused prototype and evaluate it against realistic examples.
- 03
Integrate
Connect the capability to your data, permissions, interfaces, and systems.
- 04
Operate
Monitor quality, usage, cost, and change as the solution moves into practice.
Start with the work