AI Automation
AI Automation Tested on Your Real Data, Live in 21 Days
Lead response, qualification, routing or internal workflow automation, built into your systems and tested against your historical data and real edge cases before it touches a live decision. Live on the date promised for your tier, or your next revision round is free.
Most AI automation looks great in a demo and falls apart on real, messy data. Leads get misrouted, qualification calls come back wrong, and your team spends its time correcting output instead of saving time. Nobody can tell you how accurate it really is, because it was never tested on your data.
Every misrouted lead is lost revenue, and every AI answer that needs manual correction is staff time spent undoing the automation. For high-stakes work, an untested automation is a liability. The cost of skipping testing arrives later, as errors your customers see.
I build AI-driven automation into your real systems and test it against your own historical data and edge cases before it goes live. Accuracy targets are set in writing up front, human-in-the-loop checkpoints match the risk of each decision, and you get documented test results, not promises.
Built with
What's included
What you get.
Strategy and scoping
- Discovery and audit of the workflow to be automated
- Accuracy and reliability targets defined in writing
Design
- AI workflow design mapped to your systems and data
- Risk level assessed, with human review points defined
Build and integration
- Automation built into the systems the workflow touches
- Secure connections and error handling
Real-data testing
- Testing on your historical data, not synthetic or demo data
- Systematic tests against real edge cases, not just the happy path
Safeguards
- Human-in-the-loop checkpoints calibrated to the stakes
- Fallbacks when the automation is unsure
Handoff and documentation
- Documented accuracy and reliability results
- Handoff documentation and a walkthrough for your team
Not included
- Ongoing AI model or API usage costs
- General-purpose chatbots or content generation
- Guaranteed accuracy outside the tested scenarios
Outcomes
What changes.
A working automation you can trust, with documented accuracy from real-data testing
Fewer misrouted or misqualified leads
Less staff time spent correcting AI output
Human review exactly where the risk is high, and nowhere else
Clear results in writing, so you know what it can and cannot do
Process
How it works.
Discovery and audit
A short assessment of the workflow, your available data and its risk level. You get a launch date.
Design and build
The workflow is designed with accuracy targets and built against your systems.
Test on real data
Systematic testing on your historical data and edge cases, with results documented.
Launch and monitor
The automation goes live with human-in-the-loop checkpoints and a plan for monitoring as real data drifts.
Why me
About Me.
I've spent my career at the intersection of software architecture and business strategy — leading engineering teams, rebuilding fragile systems into scalable platforms, and translating technical decisions into revenue, margin, and speed-to-market.
As a Fractional CTO, I embed with founders and leadership teams to bring senior technical judgment without the overhead of a full-time executive. That means honest audits, pragmatic roadmaps, and hands-on architecture — not just advice from the sidelines.
My focus is measurable outcomes: operations that run on autopilot, products that ship faster, and lead-generation systems that compound. If it doesn't move the business forward, it doesn't make the roadmap.
What our clients say.
Arfan didn't just advise us — he rebuilt our platform architecture and hired the team to run it. We shipped faster in six months than the previous two years combined.
Sarah Whitfield
CEO
We were drowning in manual dispatch and invoicing. Arfan automated it in weeks, not quarters, and our technicians finally have time back in their day.
Marcus Alden
Founder
As an agency, our margins live and die on process. The automation systems Arfan put in place let us take on more clients without adding headcount.
Priya Nathan
Managing Partner
Pricing
Investment.
Price range: $6,500–$20,000, depending on how many workflows are in scope, the complexity and volume of data available for testing, and how much human review the risk level requires. Most teams start with the Multi-Workflow tier.
Optional add-ons
Extra workflow
Add another workflow to your build, designed, integrated and tested on your data.
$3,000
Expedited delivery
Move your build to the front of the queue for a faster launch.
$1,000
Quarterly re-test
Re-run your test set on fresh data to confirm accuracy has not drifted.
$1,500
Monthly monitoring retainer
Ongoing monitoring, tuning and a short monthly review of automation performance.
$1,200/mo
FAQ
Common questions.
We already tried an AI tool and it didn't work. Why would this be different?
Most AI tools are never tested on real, messy production data, which is where they break. This offer tests on your own data before you trust it with anything live.
Why is this more expensive than a typical AI build?
The price reflects testing rigor, not extra scope. You are paying for an automation with documented accuracy, not a demo.
How is this different from a generic chatbot?
A chatbot answers questions. This automates a specific workflow inside your systems, such as lead response or routing, with defined accuracy targets and safeguards.
Can you guarantee accuracy?
No tool is perfect. What I guarantee is delivery by the promised date and documented results from testing on your data, so you know exactly how it performs and where it needs a human.
What data do you need access to?
Historical examples of the workflow, such as past leads, outcomes or tickets, plus access to the systems it will connect to. We agree the data scope on the first call.
Why does this take longer than a simple automation?
Testing on real data and edge cases is where the time goes. It is also what prevents costly errors after launch.
Do we need this if our workflow is small?
Possibly not. The Single Workflow tier is built for one narrow workflow. If a simple tool is enough, I'll tell you on the call.
What happens if the testing shows the automation isn't accurate enough?
We refine it, add human review where it is needed, or narrow the scope. You see the results either way, so decisions are based on evidence.
Which tier should I choose?
Most teams start with Multi-Workflow. Choose Single Workflow for one narrow workflow, and Enterprise System if several teams or systems depend on the automation.
Ready to See If Your Automation Would Hold Up on Real Data?
Tell me which workflow you want to automate and what systems it touches. In a short assessment call I'll recommend the right tier and give you a launch date.