AI-First Application Development — Custom and AI-Embedded Apps

Custom and AI-embedded application development for government and regulated organizations. LLM and RAG integration, cloud-native delivery, fixed-fee, senior-led.

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Every application ships with intelligence.

Most application engagements stall in one of two places: requirements that don’t survive contact with the user, or AI features bolted on after the fact that don’t fit the workflow. We start with the workflow, design the AI surface to fit it, and ship in two-week increments your stakeholders can see and react to. We don’t sell you a 12-month statement of work and disappear into a slide deck.

What’s Included

Custom application development — full lifecycle, from product definition through production support. Web, mobile, internal tools, customer portals.

AI-embedded delivery — LLM-integrated workflows, retrieval-augmented generation (RAG), document intelligence, computer vision, conversational UX. Built into the application, not bolted on.

Legacy modernization — strangler-fig replacement of legacy systems. Incremental, with the legacy system live throughout.

Mobile and web — React, React Native, Vue, Swift, Kotlin. Stack chosen to fit your team’s maintenance reality, not our preference.

Cloud-native deployment — Terraform / CDK / Pulumi infrastructure, CI/CD pipelines, observability baked in. AWS, Azure, GCP, FedRAMP-aligned where required.

Production support — 24/7 on-call coverage available for engagements that need it. SLA-defined, transparent.

DELIVERY MODEL

Discover, build, validate, operate.

  1. Discover (2–4 weeks)

    Workflow analysis, stakeholder interviews, technical assessment, definition of MVP scope. Output: prioritized backlog and architecture brief.

  2. Build (8–24 weeks)

    Two-week increments. Demo every two weeks. Deploy to staging continuously. Scope-dependent timeline.

  3. Validate (2–4 weeks)

    UAT, security review, accessibility audit, performance testing. Production cutover.

  4. Operate (ongoing, optional)

    Production support, feature additions, monitoring, capacity planning.

Outcomes

  • A working application your users actually use, deployed to production with monitoring and a runbook.
  • A team that can take it over from us — clean code, documented decisions, no mystery dependencies.
  • AI features that earn their keep on every workflow they touch, not features added because they were on the deck.

Frequently Asked Questions

What stacks do you work in? TypeScript / React / Next on the front end. Node, Python, Go, Java, .NET on the back end. We choose for your team’s maintenance reality, not ours.

Do you do greenfield or just modernization? Both. About half our engagements are greenfield, half are legacy modernization.

How is “AI-embedded” different from “we use AI”? AI-embedded means the AI surface is part of the workflow design from the start. Bolted-on means it was added at the end and feels like it. We do the former.

Can you work with our existing engineers? Yes. Most engagements pair our seniors with your engineers. Knowledge transfer is part of the deliverable, not a surcharge.

Do you do design, or just engineering? We have product designers. We can also work alongside your design team if you have one.

Ready to talk — or still evaluating?

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Tell us what you're working on. Security, modernization, staffing — whatever it is, you'll hear back from a senior person within 48 hours. Not a sales rep. Not a chatbot.

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