Gen AI · Step 02 Build

GenAI / ML Build.

Design and build secure, scalable GenAI / ML production applications.

Powered by AWS

Built with

  • Amazon Bedrock
  • Amazon SageMaker
  • AWS Lambda
  • Amazon ECS
AWS Partner, Advanced Tier ServicesAWS Partner, Generative AI Competency, via Ingram Micro

Why it matters

Why it matters.

Demos prove interest.

Production proves value, and the gap between them is where most GenAI budgets disappear.

Building it right the first time means security, evaluation and cost control are designed in, not retrofitted after launch.

Your engineers work alongside ours, so the system stays maintainable once we step back.

What’s included · how it runs

Design. Build. Harden. Launch.

Typically 6–8 weeks

  1. Step 01

    Design

    Lock the architecture, success metrics and cost envelope.

    What’s included

    Solution design

    Target architecture on AWS covering models, retrieval, orchestration, security and cost.

  2. Step 02

    Build

    Deliver in short iterations with working software reviewed every week.

    What’s included

    Embedded build

    Our engineers build alongside yours in your repos, your pipeline, your standards.

  3. Step 03

    Harden

    Security review, evaluation, load testing and failure handling.

    What’s included

    Evaluation harness

    Automated quality checks in CI so regressions are caught before customers find them.

    Production hardening

    Guardrails, rate limits, fallbacks, observability and load testing before go-live.

  4. Step 04

    Launch

    Ship to production and hand over ownership with documentation and dashboards.

    What you walk away with

    • Production GenAI application on AWS
    • Infrastructure as code and CI/CD
    • Automated evaluation suite
    • Runbooks, dashboards and team handover

Case studies

Customers we’ve delivered this for.

All case studies
Draft · pending HES approval
Case studyHuman eSources

Make the hiring call with AI.

How Human eSources turned nearly three decades of talent science into AI that explains every job match, live on Amazon Bedrock behind TruTalent, its new recruiting platform.

Industry
HR tech, talent assessment
We built
Talent Scout AI
Runs on
Amazon Bedrock
Read the case study
Keith Gaudreau, VP Product Strategy, Human eSources
Human eSources

Keith Gaudreau

VP Product Strategy

Case studyMould Detect AI

Computer vision for mould detection.

[How the client got the outcome: what Assembly built and where it runs. One sentence.]

Talk to an engineer
[First Last][Role]
Case study[Client]

[The promise] [in 2 lines].

[How the client got the outcome: what Assembly built and where it runs. One sentence.]

Talk to an engineer
[First Last][Role]

Funded by AWS · for eligible companies

Funded.

Start with a GenAI/ML Readiness Assessment, funded by AWS if you qualify.

Check if you qualify

Funding is subject to AWS approval. We check your fit with you before anything goes to AWS.

Let’s talk about GenAI / ML Build.

A 30-minute call is usually enough to tell you whether this is the right next step, and what it would cost.