How I Built an AI Sales Advisor Using DeepSeek + Vercel — and What I Learned from 30 Years of B2B Deals

#webdev #opensource #ai #productivity

I remember a deal I lost in 2018 — a $2M automation project in Guangzhou. I had the best product, the best price, and I lost it. Not because of the competition. Because I never figured out that the real decision maker wasn't the VP of Engineering — it was the CFO who sat in on only one meeting and never spoke. That loss cost me six months of work. Cliento was born from that loss.

The Problem I Kept Seeing

After 30+ years closing complex B2B deals in industrial automation, robotics, and enterprise software, I kept watching the same thing happen:

Talented sales reps losing deals they should have won.

Not because of lack of effort. But because at 9pm before a critical meeting, there was no senior advisor to call. No one to help diagnose why a deal went cold. No framework to figure out who the real decision maker was.

So I built Cliento — an AI Sales Advisor that puts 30 years of real deal experience into the hands of every B2B sales rep.

What Cliento Does

Cliento is a conversational AI coach for B2B account executives navigating complex, multi-stakeholder deals.

Ask it anything about a live deal:

"How do I find my real target customers?"
"Who is the internal champion in this account?"
"Why did this deal suddenly go cold?"
"How do I prepare for a meeting with the CFO?"

Every response follows a structured format:

Core Issue — what's really going on
Sharp Questions — what you need to ask yourself
Direction — what to do next

The Tech Stack

Layer	Technology
Frontend	Single-page HTML/CSS/JS
AI Model	DeepSeek (deepseek-chat)
API Proxy	Vercel Serverless Function
Hosting	Vercel (free tier)

Total infrastructure cost: near zero.
Deployment time: under 5 minutes.

Why DeepSeek?

I chose DeepSeek for three reasons:

Cost — fraction of GPT-4 pricing for similar output
Speed — fast response times for conversational use
Reasoning quality — surprisingly strong at structured sales reasoning when given the right prompts

The secret isn't the model. It's the prompt engineering built on 30 years of real sales frameworks.

The Architecture

export default async function handler(req, res) {
  const response = await fetch(
    'https://api.deepseek.com/chat/completions', {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env.DEEPSEEK_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      model: 'deepseek-chat',
      messages: req.body.messages
    })
  });
  const data = await response.json();
  res.json(data);
}

Simple. Secure. No API key exposed to the client.

The 10 Questions Cliento Answers

These are the real questions that win or lose B2B deals:

How do I find my target customers?
How do I uncover real pain points?
What background questions confirm a real opportunity?
How do I ask diagnostic questions?
Who is the internal champion?
How do I prepare for the key decision maker?
What's my logic for saying this deal is 75% likely to close?
How do I handle last-minute negotiation obstacles?
How do I reach a win-win agreement?
How do I debrief what I won and lost?

What I Learned

Building this taught me something unexpec
ted: the hardest part wasn't the code. It was distilling 30 years of sales intuition into structured prompts.

Every framework, every diagnostic question, every coaching sequence had to be precise enough that an AI could deliver it consistently — and honest enough that a senior sales leader would recognize it as real.