I built an AI phone receptionist in 3 weeks. Here's what nobody tells you.

Abbas Imran — Tue, 12 May 2026 13:37:04 +0000

I want to share something I've been working on for the past few weeks, mostly because I couldn't find a single honest write-up about it when I started. So here's mine.

A client came to us with a really specific problem. They were losing leads. Not because their service was bad actually, the opposite. They were so good that their phone never stopped ringing, and a small team of two people couldn't pick up every call. The owner told me, almost embarrassed, that he'd been answering calls at 11 PM the night before because he didn't want to miss a sale.

That hit me in a way I didn't expect.

So we said, okay, let's build an AI that answers the phone like a real person. Books appointments. Qualifies leads. Tells callers what they need to know. Doesn't sound like a robot. And does it for under what a part-time receptionist would cost.

Three weeks later, we shipped it. Here's the honest story.

Why I almost gave up in week 1

I'd built voice apps before. I thought this would be easy. Twilio for the phone line, GPT-4o for the brain, some TTS for the voice done.

Lol.

The first version we built worked exactly once, in the staging environment, with a perfect WiFi connection and me speaking in a clean American accent into a $200 microphone. The moment a real customer called in from a noisy car with a British accent, the whole thing collapsed.

Three things broke immediately:

Latency. Standard TTS pipelines add 600-1200ms before any audio comes back. On a phone call, that feels like the line went dead. People hung up.
Interruptions. Real humans interrupt. Real humans say "uhh" and "wait, actually." Our agent waited politely for them to finish, which they never did.
Hallucinations on critical data. The agent confidently told a caller our office was open Sundays. We are not open Sundays.

I closed my laptop at 2 AM and considered emailing the client to ask for an extension. Instead I made coffee and started over.

"Coffee fixes everything except your code."

The stack that actually worked

After three iterations, here's what stuck:

Twilio for the carrier layer (porting numbers, SIP, programmable voice)
OpenAI Realtime API for speech-to-speech (this changed everything more on this below)
LiveKit for WebRTC audio routing (because Twilio's media streams alone have weird buffering)
Node.js for the orchestration layer
Postgres + Redis for state and call session tracking

The single biggest unlock was the Realtime API. Once we stopped doing the old audio → STT → LLM → TTS → audio pipeline and switched to native speech-to-speech, our perceived latency dropped from ~1.5 seconds to about 350ms. That's the difference between "this feels like a robot" and "wait, is this a person?"

The webhook that started it all

This is the entry point. When Twilio receives a call, it pings our webhook, and we hand off the call to LiveKit which then bridges to the realtime model.

// app/api/voice/incoming/route.ts
import { NextRequest, NextResponse } from "next/server";
import { generateLiveKitToken } from "@/lib/livekit";

export async function POST(req: NextRequest) {
  const formData = await req.formData();
  const callSid = formData.get("CallSid") as string;
  const from = formData.get("From") as string;

  // create a session row so we can track the call later
  const session = await db.callSession.create({
    data: { callSid, from, startedAt: new Date() },
  });

  const token = await generateLiveKitToken({
    room: `call-${session.id}`,
    identity: `caller-${from}`,
  });

  // hand the call off to our LiveKit room
  const twiml = `
    <Response>
      <Connect>
        <Stream url="wss://livekit.example.com/twilio?token=${token}" />
      </Connect>
    </Response>
  `;

  return new NextResponse(twiml, {
    headers: { "Content-Type": "text/xml" },
  });
}

Looks simple. Took me four days to get right.

Teaching the agent the business

This is the part that I think most tutorials skip, and it's the most important part.

The model is smart. The model does not know your business. We had to give it a "brain file" a structured prompt that combined business hours, services offered, pricing rules, escalation paths, and behavior guardrails. We also gave it function-calling tools so it could actually do things, not just talk about them.

const tools = [
  {
    type: "function",
    name: "book_appointment",
    description: "Book a service appointment in the calendar",
    parameters: {
      type: "object",
      properties: {
        customer_name: { type: "string" },
        phone: { type: "string" },
        service: { type: "string", enum: SERVICES },
        preferred_date: { type: "string", format: "date-time" },
      },
      required: ["customer_name", "phone", "service"],
    },
  },
  {
    type: "function",
    name: "escalate_to_human",
    description: "Transfer to a human agent for sensitive or complex cases",
    parameters: {
      type: "object",
      properties: {
        reason: { type: "string" },
      },
    },
  },
];

The escalate_to_human tool was the one that earned the client's trust. We baked in rules: any pricing dispute, any angry caller, any mention of legal escalate. The agent doesn't try to be a hero. It knows when to tap out.

The interruption problem

This took me a full evening to solve and I'm still not 100% happy with it.

Real humans interrupt. If you don't handle interruptions, your agent feels like it's lecturing them. We used voice activity detection to cut the agent off mid-sentence when the caller starts speaking, then resumed the conversation from where the caller left off not from where the agent was.

session.on("user_speaking_started", () => {
  if (agentIsSpeaking) {
    session.cancelResponse();
    agentIsSpeaking = false;
  }
});

Two lines. One evening of debugging. I'm not proud, but I'm tired.

What I'd do differently

A few honest takeaways:

Don't try to make it sound exactly human. Tell callers it's an AI in the first 5 seconds. Trust goes up, not down. The ones who care will appreciate the honesty. The ones who don't will keep talking.
Log every single conversation. We were debugging hallucinations from memory for three days before we set up proper transcript logging. Don't be us.
Edge cases are 60% of the work. "What if they don't speak English?" "What if they say a number wrong?" "What if they're on speaker phone?" We have a 47-item edge case checklist now.
Latency matters more than intelligence. A slightly dumber model that responds in 300ms feels better than a smarter one that takes 1.2s.

Where we are now

The agent has been live for two months. It answers about 80 calls a day. It books roughly half of them as actual appointments. The client tells me he sleeps through the night now, which honestly is the metric I care about most.

Was it worth three weeks of evenings and one mild breakdown at 2 AM?

Yeah. It was.

If you're building something similar, feel free to reach out. I'm Abbas, I run engineering at Seedinov we build AI products for small teams who can't hire a Big Tech AI department. You can see the voice agent work in our portfolio or drop us a line if you want to talk shop.

Good luck out there. Build the thing.

How AI is Revolutionizing Digital Marketing in 2026

Abbas Imran — Fri, 06 Feb 2026 13:08:22 +0000

How AI is Revolutionizing Digital Marketing in 2026

The digital marketing landscape has undergone a massive transformation with the advent of artificial intelligence. At Seedinov, we've been at the forefront of implementing AI-driven solutions that deliver measurable results for our clients.

The Rise of AI in Marketing

Artificial intelligence is no longer a futuristic concept—it's here, and it's changing how businesses connect with their audiences. From personalized content recommendations to automated campaign optimization, AI is making marketing smarter and more efficient.

Key Statistics

80% of marketers now use AI tools in their daily operations
AI-powered campaigns see an average 30% increase in ROI
Automated content generation has reduced production time by 60%

How Seedinov Leverages AI for Your Success

At Seedinov, we integrate cutting-edge AI technologies into our digital marketing services to help businesses scale efficiently.

1. AI-Powered Content Creation

Our content marketing solutions use advanced AI to:

Generate SEO-optimized blog posts
Create engaging social media content
Develop personalized email campaigns

2. Predictive Analytics

Understanding your audience is crucial. Our analytics services leverage machine learning to:

Predict customer behavior patterns
Identify high-converting audience segments
Optimize ad spend in real-time

3. SEO Automation

Search engine optimization is evolving rapidly. Our SEO services now include:

Automated keyword research and tracking
AI-driven content optimization
Intelligent backlink building strategies

Real Results: A Case Study

One of our clients, a B2B SaaS company, saw remarkable improvements after implementing our AI-driven marketing strategy:

Metric	Before	After	Improvement
Organic Traffic	5,000/mo	18,000/mo	+260%
Lead Generation	50/mo	180/mo	+260%
Domain Authority	25	42	+68%

"Seedinov's AI-powered approach transformed our digital presence. The results exceeded our expectations." — Marketing Director, Client X

Getting Started with AI Marketing

Ready to harness the power of AI for your marketing efforts? Here's how to begin:

Audit your current strategy - Identify areas where AI can add value
Start small - Implement one AI tool at a time
Measure and iterate - Track results and optimize continuously
Partner with experts - Work with specialists who understand AI

Conclusion

AI is not replacing marketers—it's empowering them to achieve more. By combining human creativity with artificial intelligence, businesses can create more effective, personalized, and scalable marketing campaigns.

Want to explore how AI can transform your marketing? Contact Seedinov today for a free consultation.

Connect with us:

Website: seedinov.com
LinkedIn: Seedinov on LinkedIn
Twitter: @seedinov

DEV Community: Abbas Imran

I built an AI phone receptionist in 3 weeks. Here's what nobody tells you.

Why I almost gave up in week 1

The stack that actually worked

The webhook that started it all

Teaching the agent the business

The interruption problem

What I'd do differently

Where we are now

How AI is Revolutionizing Digital Marketing in 2026

How AI is Revolutionizing Digital Marketing in 2026

The Rise of AI in Marketing

Key Statistics

How Seedinov Leverages AI for Your Success

1. AI-Powered Content Creation

2. Predictive Analytics

3. SEO Automation

Real Results: A Case Study

Getting Started with AI Marketing

Conclusion