AI Feature Build: Production AI Agents Inside Your Product by Dominic SereAI Feature Build: Production AI Agents Inside Your Product by Dominic Sere
AI Feature Build: Production AI Agents Inside Your ProductDominic Sere
Cover image for AI Feature Build: Production AI Agents Inside Your Product
An AI feature that works in production, not just in a demo: a voice agent, a chat assistant, or an automated workflow inside your product.
Examples
A voice agent that answers, qualifies or books calls
A chat assistant inside your app, connected to your data
An automated workflow that replaces a manual back-office task
What makes it production-ready
Guardrails and escalation to a person when the conversation needs one
Scripted test conversations run before every change goes live
Logging and an audit trail for every interaction
This is the standard I hold my own AI voice platform to on live calls in a regulated industry.
Timeline
Week 1: use case, success metric, design and integration plan
Week 2: build and integrate
Week 3: testing, tuning and go-live
You provide: access to the systems the agent connects to and one decision-maker for approvals. AI and telephony usage is billed at cost, separately, with an estimate before anything is spent.
FAQs

Starting at$6,000
Duration3 weeks
Tags
Next.js
Python
Retell
AI Agent Developer
AI Automation
AI Voice Developer
Fullstack Engineer
Service provided by
Dominic Sere The Woodlands, USA
6
Followers
AI Feature Build: Production AI Agents Inside Your ProductDominic Sere
Starting at$6,000
Duration3 weeks
Tags
Next.js
Python
Retell
AI Agent Developer
AI Automation
AI Voice Developer
Fullstack Engineer
Cover image for AI Feature Build: Production AI Agents Inside Your Product
An AI feature that works in production, not just in a demo: a voice agent, a chat assistant, or an automated workflow inside your product.
Examples
A voice agent that answers, qualifies or books calls
A chat assistant inside your app, connected to your data
An automated workflow that replaces a manual back-office task
What makes it production-ready
Guardrails and escalation to a person when the conversation needs one
Scripted test conversations run before every change goes live
Logging and an audit trail for every interaction
This is the standard I hold my own AI voice platform to on live calls in a regulated industry.
Timeline
Week 1: use case, success metric, design and integration plan
Week 2: build and integrate
Week 3: testing, tuning and go-live
You provide: access to the systems the agent connects to and one decision-maker for approvals. AI and telephony usage is billed at cost, separately, with an estimate before anything is spent.
FAQs

$6,000