For mid-size and enterprise teams
AI agents that run inside your cloud, under your rules.
I design and build agents for teams with real systems and real reviewers. Your data stays in your accounts, and every step is traced.
- Start here
Architecture review
A written plan for your systems, data flow and risks, with a fixed quote for the build.
1 to 2 weeksYour tech lead joins the calls - Then
Pilot build
One agent in your cloud, tested on your own past cases before it goes live.
4 to 6 weeksYour team owns the repo - Ongoing
Retainer
Fixed hours each month for changes, test runs and a monthly report.
MonthlyHours agreed in writing - The price for each is set after the scoping call. You get it in writing.
How it runs in your environment
Watch a real run move through the system.
This is run 1153 of my own lead agent, recorded step by step. It took 13.5 seconds and 32 steps. Each line in the log lights up its part of the diagram.
- 0.10 sTrigger: website contactok
- 0.17 sQualify: AI lead scoring2.5 s
- 2.66 sQualify: parse outputtier: HOT
- 2.70 sGuard: check replypass
- 2.73 sConfig: fetch settingsok
- 3.02 sAlert: owner told0.7 s
- 3.82 sCRM: save lead2.0 s
- 6.14 sVisitor: AI reply written2.3 s
- 8.45 sVisitor: AI checker1.4 s
- 9.87 sVisitor: send email3.2 s
- 13.10 sRun: save recordai_sent
11 of 32 steps shown. Names removed.
How I test
Tested before it ships, and watched after.
You agree the pass bar before I build. The agent goes live only when it meets that bar on your own past cases.
A test set from your cases
I build a test set from your real past enquiries. We agree the pass bar together.
Tests run before each deploy
Automated tests run on every change. A failed test stops the deploy.
Every run is traced
You can open any run and see each step. A person reviews a sample each week.
$ just test --all All tests passed, 0 failed run before every deploy · my own systems
Your data, step by step
You can see where each piece of data goes.
The numbers match the run above. See the full security page →
Risk and rules
The known agent risks, each with a control.
I use the OWASP Top 10 for Agentic Applications (2026) as my checklist. Here are five. The security page lists all ten.
Working with one person
One engineer, with the paperwork your team needs.
You talk to the person who designs, builds and supports your system. Your team keeps everything needed to run it.
Moin Dalal
- Agentic AI engineer, based in India (IST)
- Online for the US and UK morning
- Joins your team calls at those times
- Designs, builds and supports your system
I sign your forms
- Your NDA, before we share anything
- Your MSA and your DPA
- EU and UK transfer clauses (SCCs)
- You own the code and the IP once paid
Your team can run it without me
- Code in your repository from day 1
- A written runbook and the test set
- A handover call with your engineers
- You can remove my access at any time
Questions reviewers ask
Short answers for your security review.
Can it run in our own cloud?
Yes. I build on AWS, Azure or Google Cloud, in accounts your team creates for me.
Do you work under our SSO?
Yes. I use the accounts and access rules you give me. You can remove my access at any time.
Which AI model provider sees our data?
Yours. The agent calls your own Azure OpenAI, Bedrock, Vertex or direct provider contract. Team projects use no third-party router.
Do you hold SOC 2?
No. The agent runs inside your cloud, under your own controls. The security page shows what I do instead, with evidence for each row.
Will you answer our security questionnaire?
Yes. I have a filled-in standard questionnaire ready, and I answer yours in full.
Who owns the code?
You do, once paid. The code is in your repository from the first day.
Start
Book a 45-minute scoping call.
- Tell me about your systemsTwo minutes. No payment.
- We talk for 45 minutesBring your tech lead or security reviewer.
- You get a written scope and priceWithin 3 working days of the call.