Real projects. Real timelines. Real outputs. Every showcase below was built with CEO.ai — so you can see exactly what's possible before you commit a dollar.
We don't cherry-pick the highlight reel. For each showcase, you'll see:
What we described to the CEO Agent — so you can see how simple the input is.
Architect selection, task breakdown, agent assignments — so you understand the orchestration.
Every component generated — so you see the full scope of output.
First pass and refinement — so you can set realistic expectations.
Where the first pass fell short and how we fixed it — so you trust us to be honest.
What the working product looks like — so you can judge the quality yourself.
Why we show the refinements: Because we'd rather be honest than impressive. The first pass is typically 80–95% of the way there. The refinement process — updating RAG knowledge, continuing conversations with specific agents — is part of how the system works and gets smarter. We think that's more valuable to you than a polished demo that hides the reality.
From Natural Language Messages to CRM Records — Fully Automated
A sales team receives leads through Telegram conversations — names, companies, interests, follow-up notes — all in messy, natural language. Someone on the team has to read every message, extract the relevant data, format it, and manually enter it into Salesforce. It takes 5–10 hours per week. Leads get missed. Follow-ups get delayed. Revenue leaks.
"Build an app that captures lead information from Telegram conversations in natural language, transforms the data using an AI agent on the backend, and automatically inserts structured lead records into a connected Salesforce account. Include a simple frontend for monitoring, a database for lead storage, and deploy on AWS."
That's it. One description. Plain language.
Selected the best architect agent from the available agent pool based on the project requirements
The architect generated a full specification — system architecture, data models, API contracts, integration requirements, deployment configuration
The architect created a detailed task list — broken into discrete sub-tasks across frontend, backend, database, infrastructure, and integrations
The CEO Agent assigned each sub-task to the best available agent for that specific type of work
All agents executed in parallel — each working on their assigned tasks
Complete code was committed to GitHub with full commit history — every file, every component, traceable
Monitoring dashboard for viewing captured leads, status tracking, and manual review interface
Schema design + migrations for lead storage, conversation tracking, and processing status
Backend logic for Telegram webhook ingestion, AI-powered NLP, data transformation, and Salesforce API calls
RESTful endpoints connecting Telegram webhooks → Lambda processing → Salesforce insertion
Complete infrastructure-as-code — Lambda, API Gateway, DynamoDB, IAM roles, all configured
Telegram Bot API + Salesforce REST API with OAuth handling
Time to first working output: approximately 60 minutes
Was the first pass perfect? No. Here's what happened:
What was ~90% right:
Architecture, database design, Lambda logic, Terraform configs, API Gateway setup, and the core Telegram → Transform → Salesforce pipeline all worked
What needed refinement:
Some edge cases in natural language parsing (inconsistent name formats), a few Salesforce field mappings that didn't match our specific org configuration, and a frontend component that needed styling adjustments
What we did:
Updated the RAG knowledge of the architect agent with more specific documentation about our Salesforce field structure and added examples of the messy Telegram message formats we actually receive
Second pass result:
Re-ran the project with the updated architect knowledge. The second output handled the edge cases correctly and matched our Salesforce configuration. ~60 minutes for the second pass.
Total time from idea to near-perfect working app: approximately 2 hours.
| Traditional | CEO.ai | |
|---|---|---|
| Timeline | 2–4 weeks | ~2 hours |
| Cost | $8K–$25K | Included in plan |
| Components | Usually backend only | Full stack in one shot |
| Maintenance | Requires dev availability | Update RAG, re-run |
| Learning | Starts from scratch | Agent retains knowledge |
The Takeaway: This isn't a toy demo. This is a production-grade application with frontend, backend, database, infrastructure, and two third-party integrations — generated from one plain-language description and refined in one iteration. The architect agent that built it now permanently knows our Salesforce configuration and Telegram message formats, making every future project faster and more accurate.
Own Every Pixel. Own Every Lead. Kick Off AI Workflows at First Contact.
Most businesses rely on third-party form tools — Typeform, HubSpot, Calendly pop-ups — for their contact forms. That means you're stuck with someone else's styling, their data policies, their rate limits, and zero ability to trigger custom workflows when a submission comes in. Want to instantly kick off an AI agent to qualify a lead, enrich the data, or route it to the right team member? You can't.
A fully custom, embeddable contact form widget where:
Responsive, brand-matched contact form component with validation, loading states, and success animations
Backend API endpoint with origin validation — rejects any request not from our domain
On submission, kicks off AI agents for lead qualification, data enrichment, and intelligent routing
Chained workflows — qualify → enrich → route → draft follow-up — all triggered at first point of contact
All submissions stored in our database with full audit trail of every agent action taken
Initial build by CEO Agent
Full widget + API + agent triggers — first working version
RAG upskilling + refinement
Training agents on our qualification criteria, routing rules, and brand voice
Integration, testing + launch
Domain locking, embed on site, end-to-end workflow testing, go live
Total time from zero to live: ~11 hours
This isn't just a contact form. It's a fully owned first-touch intelligence layer:
Zero third-party dependency — no Typeform fees, no HubSpot lock-in, no worrying about someone else's uptime or data policies
AI workflows fire at the moment of contact — leads get qualified, enriched, and routed before your team even sees them. No more manual triage.
Total styling control — it looks exactly like your brand because it is your brand. No CSS hacks to hide someone else's logo.
Every form submission on your site could be the start of an intelligent workflow. Why would you hand that to a third party?
Multiple AI Agents Collaborating to Run Your Entire Content Pipeline
Creating consistent, high-quality content across 5+ channels is a full-time job. You need to monitor trends, align them with your strategy, create briefs, write platform-specific drafts, get CEO approval, publish, then track what's working and adapt. Most companies either hire a content team (expensive) or let content fall off a cliff after the first month (common). The CEO of a growing company doesn't have time to do it all — but they're the voice the audience wants to hear.
A multi-agent content pipeline where multiple CEO AI Agents work together across two interconnected workflows:
Monitors X, LinkedIn, Reddit, and industry news for trending topics and audience signals
Trained on brand pillars and positioning — maps trends to content opportunities and prioritizes them
Generates channel-specific briefs for LinkedIn, X, blog, newsletter, and short-form video
Writes finished drafts in the CEO's voice — RAG-trained on past content, tone guide, and brand language
Pulls weekly + monthly performance metrics across all channels and generates performance reports
Analyzes what's working, identifies gaps, and feeds recommendations back into the strategy loop
Visual calendar with all scheduled content, draft status, and one-click approve/edit/publish for the CEO
Agent Collaboration Flow
6 AI Agents working together — from trend to finished draft, continuously improving
CEO time on content
→ 15 min/day reviewing and approving (down from 2+ hrs)
Content output
→ 5 channels, consistent publishing, zero content gaps
Strategy adaptation
→ Automatic weekly pivots based on real performance data
Content team replaced
→ Strategy lead + writer + social manager + analyst = 6 AI agents
A content team doing this work across 5 channels costs $8,000–$15,000/month. Six AI agents working together on CEO.ai cost a fraction of that — and they never miss a deadline.
This is what multi-agent orchestration looks like.
We use our own platform daily — because the best way to prove what it can do is to keep building with it. Here's what's in the pipeline:
AI agents monitoring stock levels, predicting reorders, and generating purchase orders
From signed contract to fully provisioned project workspace in minutes
Ingest contracts, extract key terms, flag risks, populate a review dashboard
Specialized agents handling billing, technical, and product questions with intelligent routing
Want to suggest a project? Tell us your use case on a setup call and we might build it as our next showcase — with your input shaping the result.
Suggest a Project / Book Your CallMost businesses underestimate the cost of their manual processes by 3–5×. When you factor in time, errors, missed opportunities, and the compounding effect of slow execution — the real number is usually painful.
Take one manual process your team does weekly.
Multiply the hours spent × the fully-loaded hourly cost of the people doing it × 52 weeks.
That's your annual cost for ONE process.
Now imagine automating 4 of those.
We're a young platform earning trust through transparency. Instead of fabricated quotes, we show real projects with real timelines and real refinement stories. As our first customers get results, their stories will appear here.
Every business has different bottlenecks, different tools, different workflows. The showcases above prove the platform works. Your setup call is where we figure out exactly how it works for you.
30 minutes. No pressure. Real answers.
Every plan includes guided setup. Most customers are live within one week.