Agent Readiness Sprint
Two weeks: one workflow mapped, data and systems checked, a costed build plan.
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Production AI systems on Amazon Bedrock and Microsoft Foundry
Take AI from pilot to production, then keep it running, with security, monitoring, evaluation and cost control.
When to bring us in
Your AI pilot works in a demo, not in production
Security, monitoring, evaluation and cost control on Amazon Bedrock or Microsoft Foundry.
ClaimXPro.ai
An Amazon Bedrock feature live in a claims platform, behind a feature flag and role checks.
AI has to run inside your own cloud and data rules
We build in your AWS or Azure account and choose models by your cloud, data rules and cost.
ClaimXPro.ai
Claude Haiku 4.5 through Amazon Bedrock, called from the platform’s own NestJS backend.
You need someone to run it after launch
Monthly AgentOps: we run, monitor and improve your agents, and report on quality and cost.
ClaimXPro.ai
Ongoing release batches across web and iOS, QA-checked on staging and again in production.
How does AI go from pilot to production?
Four steps, plus the evaluation and monitoring that keep the system safe to run every day.
Production hardening
Security, access control, monitoring, evaluation and fallbacks before full rollout.
How do we ship AI without breaking things?
Every change goes through Git, code review, automated tests and staging. AI drafts code; an engineer reviews every change before release.
Book a discovery callStep 01
Discover
Map the workflow, data and systems before writing any code.
Claude
Step 02
Plan
Scope, fixed estimate and success measures agreed with you.
Step 03
Build
Small, reviewed changes. AI-assisted, engineer reviewed.
Git
Docker
Step 04
Test
Automated tests, plus evaluation runs on AI output.
- Playwright
PHPUnit
Step 05
Ship
Planned releases with a tested rollback.
GitHub Actions
Step 06
Monitor
Errors, latency, cost and AI answer quality watched after release.
- CloudWatch
How an AI agent project runs, step by step
- Agent Readiness Sprint, 2 weeks. We map one workflow, check your data and systems, and hand you a costed build plan.
- Agent Pilot, 4 to 6 weeks. One agent built against your real systems and data, tested with your own team.
- Production hardening, scoped per pilot. Security, access control, monitoring, evaluation and fallbacks before full rollout.
- AgentOps, monthly. We run, monitor and improve your agents, and report on quality and cost.
AI we run in production
ClaimXPro, one of 100+ projects delivered, runs an Amazon Bedrock feature in a live claims platform.
See all projects
Case 01Custom build
ClaimXPro.ai
Claims and restoration platform on web and iOS, with Amazon Bedrock in the technician workflow
- Property restoration
- Next.js
- Australia
How the ClaimXPro AI feature is guarded
- Amazon Bedrock
- Claude Haiku 4.5
- NestJS
- PostgreSQL
- Behind a feature flag, and limited to owners and admins.
- Rate-limited, with a cap on text length per request.
- Ten automatic checks run before any suggestion is shown.
- Staging first, then production releases gated on health checks, with alerting.
The stack we work in
AI platforms
- Amazon Bedrock
- AgentCore
- Microsoft Foundry
Models
- Claude
- OpenAI
Cloud and monitoring
- AWS
- Azure
- CloudWatch
Ship
- Git
- Docker
- GitHub Actions
Ways to work with us
A fixed-price sprint, a scoped build or a dedicated engineer. Start small, switch later.
Production AI questions
Why do AI pilots stall before production?
A demo skips the hard parts: access control, monitoring, evaluation, fallbacks and cost limits. Production hardening adds them before full rollout, so the system is safe to run every day.
Amazon Bedrock or Microsoft Foundry?
We choose by your cloud, data rules and cost. We build on Amazon Bedrock with AgentCore and on Microsoft Foundry Agent Service, with OpenAI and Anthropic Claude models.
How do you check AI output?
With automated evaluation runs on AI output, plus checks in code. In ClaimXPro, ten automatic checks confirm that numbers, dates, names and negations are unchanged before a suggestion is shown.
What does AgentOps include?
We run, monitor and improve your agents every month, and report on quality and cost. Errors, latency, cost and answer quality are watched after every release.
How does a production AI project start?
Most start with the Agent Readiness Sprint: two weeks, fixed scope, fixed price. You get a costed build plan you can use with us or with any team.
What happens next
A straight answer on what to build first.
- Your workflow, systems and goals.
- We reply with times for the call.
- A fixed-price next step, or a referral if we are not the right fit.
First reply within 1 business day.
Free call. NDA on request. First call in your time zone.
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