SaaS Platform · AI & Automation

A Multi-Channel AI Customer Engagement Platform

We built a SaaS platform that puts one AI assistant in front of a company's customers wherever they show up — WhatsApp, Instagram, Messenger, email, or website chat — answering from that company's own knowledge instead of generic AI.

Built by
HashCode – FZE
Type
SaaS platform, designed and built by us and running in production
Industry
Customer engagement, sales & support automation

5+

Channels unified

24/7

Availability

Multi-tenant

Architecture

End to end

Delivery

Overview

Most businesses talk to their customers in five different places and manage them in five different tools. We set out to collapse that into one. HashCode designed and built a SaaS platform where a company can run intelligent agents across every channel its customers already use — WhatsApp, Instagram, Facebook Messenger, email, and a chat widget on its own site — all from a single dashboard.

What makes it work is that the AI actually does the job, not just small talk. It answers from the company's own knowledge base, captures and qualifies leads, opens and routes support tickets, books meetings, and brings in a human the moment a conversation needs one. It runs around the clock and replies in the customer's own language.

We own the whole stack on this one: the backend, the AI orchestration, the web app, every integration, billing, and the production infrastructure it all runs on.

The Challenge

Every channel a business uses tends to be its own island. Someone messages on Instagram, a complaint lands by email, a question comes in through website chat, and none of those tools know the others exist. Replies get slow, leads slip through the cracks, answers contradict each other, and nobody has one clear view of the customer. We needed a platform that could:

  • Answer instantly and accurately on any channel, using the business's own content instead of generic AI guesses.
  • Turn conversations into real outcomes — qualified leads, deals, tickets, booked meetings — not just chat logs.
  • Give the team genuine analytics and AI insight across every channel at once.
  • Work as a multi-tenant, white-label product from day one, so it could be rebranded and resold.
  • Hold up in production at scale, and handle customer data and third-party credentials safely.

The Solution

We built it in clean layers, keeping the business logic away from any one framework or vendor so nothing was painted into a corner. Here's how the pieces fit together.

One AI brain, every channel

A single shared pipeline processes messages from every channel, so an agent behaves the same on WhatsApp as it does in website chat. The agents run on large language models with function calling and a central tool registry, which means the AI doesn't just reply — it acts. It looks up an answer, creates a lead, opens a ticket, or books a slot, then carries on.

Answers from the customer's own knowledge

Every response is grounded in the business's own uploaded content through a vector-search retrieval layer, so the AI isn't making things up. Ask a question in one language and you get the answer back in that same language.

Conversations that become outcomes

A chat shouldn't die as a transcript. The platform ships with a CRM (leads, deals, and AI lead scoring), support and agent ticketing with SLA tracking, routing and escalation, surveys, and calendar booking that even preps the AI before the meeting.

Numbers you can actually ask questions of

Alongside the marketing and cross-channel analytics, there's a “chat with your data” feature: someone can ask about their own numbers in plain English and get an answer, instead of building a report to find it.

Rebrandable to the core

The whole product is configuration-driven, so the same codebase can go out as a completely different brand — its own name, logo, colors, domain, legal entity, and pricing. We proved it in production by running a fully rebranded deployment on the very same infrastructure.

Built to be run, not just demoed

The operational side is all there: self-serve onboarding, automated billing and subscriptions, an admin panel with granular permissions and audit logging, two-factor authentication, and encrypted storage for third-party access tokens.

Technology

Technology stack used to build the platform
LayerTechnology
BackendPython, FastAPI
Async & background jobsCelery workers, Redis broker
DatabasePostgreSQL (with connection pooling)
AI / MLLLMs with function calling, vector search, voice transcription
FrontendReact, TypeScript, Vite
IntegrationsWhatsApp, Instagram, Messenger, payments, calendar, workflow automation
InfrastructureDocker, containerized web + worker services, zero-downtime deployment
Security2FA, encrypted credential storage, role-based permissions, audit trails

Under the hood it follows a clean, hexagonal architecture that keeps the AI orchestration separate from the channel integrations, so we can add a new channel or capability without disturbing the core.

Results & Impact

5+

channels running through one AI layer

24/7

answers grounded in each business's own knowledge

Multi-tenant

white-label, proven with a live rebranded deployment

Automated

billing and subscriptions, self-serve through enterprise

Why It Matters

A business can retire a whole shelf of disconnected tools — chatbot, CRM, ticketing, analytics, booking — and run all of it through one AI layer that meets customers on whatever channel they already use, in their own voice and language, at any hour. It's already live in production, and because it's multi-tenant and white-label, the same codebase can go out as a completely different product for the next client.

  • AI SaaS
  • Conversational AI
  • Automation
  • Vector search
  • FastAPI
  • Multi-tenant
  • White-label
  • CRM

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