callturaAI VOICE AGENTS · FOUNDER
Calltura
AI voice agents that answer, qualify, and route real phone calls for businesses. Built to stay up when the phones are ringing.
Read the case study →AI Systems · Production Hardening
Shipping AI prototypes to production.
You have an AI prototype that demos well and falls over under real load. You get it back as a deployment you can put in front of real users, and trust when they show up.
ABOUT
Anas Aqeel
Forward Deployed Engineer
I take AI prototypes that demo beautifully and make them survive real users. The retries, the timeouts, the log lines that tell you what actually happened. The unglamorous parts that decide whether your product survives its first busy day. Founder of Calltura, where I build AI voice agents that take real inbound calls for real businesses.
Available for August 2026
Founder of CallturaShipping AI to productionAvailable for August 2026
THE GAP
The demo was the easy part.
Prototyping AI is basically solved. Anyone can wire a model to a UI in an afternoon and get something that demos well.The hard part starts after: real users send input you didn't plan for, an API times out, costs spike, and "it works on my machine" stops being enough. The gap between a working demo and a product you can trust is where I spend my time.
WHAT I DO
I make AI features hold up in production.
Reliability
Retries, timeouts, fallbacks, and rate-limit handling, so one flaky API call doesn't take the whole feature down.
Observability
Tracing, logging, and cost tracking, so when something breaks, you know exactly where and why before a user tells you.
Real integrations
Trading mock data and the one happy path for the actual APIs, auth, and edge cases your users will throw at it.
Error handling
Graceful degradation and clear failure states, instead of a spinner that never resolves and a support ticket you can't reproduce.
Architecture & scale
Clean, boring structure a team can read, extend, and run without me in the room. Built to grow past the first launch.
Not a laundry list of frameworks. The judgment to know which of these your product actually needs first.
Talk through yours →SELECTED WORK
Systems in production.
calltura
NDAINTERNAL TOOLING · CONTRACT
Command center for a real-estate CRM
An operations command center for a US real-estate investment platform. Turns a scattered set of AI tools into one system the team runs the business on.
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NDAONBOARDING · CONTRACT
Onboarding management system
Client-onboarding portal for a US real-estate investment platform. Replaces a 46-task spreadsheet with a role-based system that auto-blocks and auto-unlocks tasks across manager and client sides.
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agent xSOCIAL MEDIA AGENTS · FOUNDER
Agent X
Four-agent pipeline that researches, drafts, publishes, and analyzes my social media across X, LinkedIn, Instagram, and Facebook. Every daily brief and every draft is approvable by email in one click. Every correction feeds back into the prompts.
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NDAVALUATION · CONTRACT
Real-estate valuation tool
Automated after-repair-value tooling for real-estate investors. Estimates property value from messy, real-world comps data.
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NDAPROPERTY PIPELINE · CONTRACT
Property pipeline platform
Full property lifecycle in one platform for a US real-estate flip firm. Replaces a decade-old PHP tool with a configurable Section-Group-Field data model, a formula engine that pulls live MLS values, and a task engine that recomputes due dates when anchor dates move.
Read the case study →// Named references anonymized pending client sign-off. Swapped in as approvals land.
HOW WE'D WORK
Three ways to bring me in.
PROJECT
Fixed scope, fixed outcome
You know what needs shipping and want it done right the first time. We agree the scope, I build it, you get something production-ready.
RETAINER
Ongoing hardening
AI is core to your roadmap and you want a steady hand on reliability, cost, and new features as you grow. A set amount of my time each month.
HOURLY
By the hour
A specific problem: an audit, an outage, a second pair of eyes on architecture. Focused help without a long commitment.
Not sure which fits? Tell me what you're building and I'll suggest the shape that makes sense. Rates depend on scope; we'll sort that out in the first conversation.
ABOUT
The parts most people skip.
You have an AI prototype that demos beautifully. Then real users touch it and it breaks. I take that fragile prototype and make it production-grade. The retries, the timeouts, the log lines that tell you what actually happened. The unglamorous work that decides whether your product survives its first real month.
By the time it's handed back, it doesn't just work in a demo. It works at 2am when no one's watching. It fails gracefully. You can see what's happening. And you can put it in front of paying customers without holding your breath.
"Anas is an extraordinary developer. He is very quick at grasping the scope of the project. He has impressed me with his exceptional sense of detail and commitment to timelines."
Dharani Malladi, Founder of Wattif.io
WRITING
Notes on shipping AI that lasts.
I write about the production side of AI engineering: the failure modes, the fixes, and what actually holds up once real users show up. Weekly, starting August 2026.
- NEWWhy your AI demo breaks in week one
- SOONWhat "production-ready" actually means for an AI feature
- SOONMCP tool escalation patterns from production
CONTACT
Have a prototype that needs to grow up?
Tell me what you're building and where it's stuck. I read everything myself and reply within a day.
Available for new projects