OutreachX

Scale Your Reach. Not Your Team.

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OutreachX

Scale Your Reach. Not Your Team.

AI-Powered Multi-Channel Campaign Automation — WhatsApp · Voice Notes · AI Phone Calls

Inspiration

Every small business owner in India has faced the same wall: you have a product worth selling, a list of potential customers, and absolutely no time or budget to reach them at scale.

We watched friends running D2C brands spend hours manually sending WhatsApp messages one by one. We saw real-estate agents copy-pasting the same follow-up text to 200 leads every morning. We saw SaaS founders paying ₹15,000/month for tools that only did one channel — and still required a developer to set up.

The breaking point was realising that broadcasting exists, but intelligent outreach doesn't — at least not for the 6+ crore Indian MSMEs who can't afford enterprise tooling.

India has 900M+ WhatsApp users, a booming startup ecosystem, and customers who expect instant, personalised communication. The infrastructure to serve that expectation — multi-channel, AI-driven, autonomous — simply didn't exist at an accessible price point.

That gap became OutreachX.

What It Does

OutreachX is an all-in-one AI campaign automation platform that lets any business launch, manage, and analyse outreach campaigns across WhatsApp, Voice Notes, and AI Phone Calls — from a single interface, in minutes.

Campaign Builder A 6-step wizard guides users from campaign title to live launch: pick channels, upload assets, write a description (AI enhances it), upload contacts via CSV, preview, and fire.

AI Content Generation Gemini 2.5 Flash refines campaign copy in your chosen tone. Text-to-Speech converts descriptions into WhatsApp-ready voice notes (OGG/Opus). AI image generation creates campaign visuals on demand.

WhatsApp Automation Bulk campaign sending with text, images, PDFs, and voice notes. Inbound replies are handled by an AI agent that uses campaign context, chat history, and your uploaded PDF knowledge base to respond accurately — 24/7, zero human intervention.

AI Phone Calls via VAPI Outbound AI calls to every contact. The agent holds natural multi-turn conversations, answers questions using your knowledge base, and logs call status (answered/missed) with full transcription and recording.

RAG (Retrieval-Augmented Generation) Upload product PDFs, guides, or FAQs. OutreachX chunks them, generates 768-dimensional embeddings via Gemini, stores them in Pinecone, and retrieves relevant context in under 100ms whenever a customer asks a question — on WhatsApp or a live phone call.

Smart Inbox Every WhatsApp reply, across every campaign, in one place. Per-contact thread view with full AI auto-reply capability.

Analytics Dashboard Real-time metrics: call answer rate, WhatsApp engagement score, messages sent, users interacted — visualised with donut and bar charts via Recharts.

Onboarding Profile Business context (type, audience, brand style, language, compliance notes) is captured once and used by the AI across every campaign — so responses always sound like you.

How We Built It

Frontend: Next.js 16 (App Router) + React 19 + TypeScript + Tailwind CSS 4 + Framer Motion. SWR for data fetching, Recharts for analytics, Clerk for authentication.

Backend: Node.js + Express server handling WhatsApp send/receive, webhook processing, and AI reply generation.

AI Stack:

  • Google Gemini 2.5 Flash — primary LLM for text generation, description enhancement, TTS, and WhatsApp AI replies
  • OpenAI GPT-4o-mini — agent orchestration inside LangGraph
  • LangChain + LangGraph — agentic RAG pipeline with a Retrieve → Respond state machine
  • VAPI.ai — outbound AI phone call orchestration
  • Sarvam AI — Indian language TTS for regional voice notes

RAG Infrastructure:

  • PDF extraction → text chunking (500 chars, 100 char overlap) → Gemini Embedding 2 (768 dimensions) → Pinecone vector DB (namespace per campaign) → cosine similarity search (top 3 chunks, <100ms)

Infrastructure: Firebase Firestore (real-time DB + analytics), Cloudinary (asset + contact file storage), Twilio (SIP voice), WhatsApp Business Cloud API, LiveKit (real-time voice streaming), FFmpeg (WAV/MP3 → OGG/Opus conversion for WhatsApp).

Challenges We Ran Into

WhatsApp Business API sandbox limits The free-tier only allows messaging pre-registered numbers. We had to architect the entire campaign flow to work within a single registered number during development, while keeping the codebase fully scalable for production multi-number deployments.

Audio format conversion for WhatsApp WhatsApp voice notes strictly require OGG/Opus encoding. Gemini TTS returns WAV/MP3. Getting FFmpeg to run reliably server-side, produce valid OGG files, upload to Cloudinary, and deliver on time before campaign send — in the right sequence — took significant debugging.

RAG latency under concurrent load Pinecone retrieval is fast in isolation (<100ms), but when combined with embedding generation, LangGraph state transitions, chat history loading, and Gemini inference — all happening per inbound WhatsApp message — the pipeline needed careful async optimisation to stay responsive.

VAPI + LangGraph agent context injection Injecting dynamic RAG context into a VAPI call's system prompt before the call connects required pre-fetching document chunks at call initiation time and constructing a fully-formed prompt — a flow that didn't have a clean documented path and required custom engineering.

Multi-turn conversation coherence Maintaining coherent WhatsApp conversations across sessions meant loading the last 20 messages, the campaign description, and RAG context simultaneously — while staying within Gemini's context window and keeping response time under 3 seconds.

Accomplishments That We're Proud Of

  • End-to-end RAG pipeline working in production — from PDF upload to live AI responses on WhatsApp and phone calls, with sub-100ms vector retrieval
  • AI phone calls that actually feel human — not IVR, not robotic. Multi-turn conversations with Sarvam + VAPI that surprised us during testing
  • Full campaign lifecycle in one platform — from a blank canvas to a live multi-channel campaign (WhatsApp + voice note + AI calls) in under 5 minutes
  • Zero manual follow-up — the Smart Inbox auto-replies to every inbound message using the full campaign + knowledge base context, completely autonomously
  • Multilingual outreach — Sarvam AI enables voice notes and calls in Hindi, Bengali, and other regional languages, making OutreachX viable for Tier-2/3 city businesses
  • Three engineers, one focused product, built and shipped in hackathon time

What We Learned

  • RAG is only as good as your chunking strategy. The 500-character chunk size with 100-character overlap wasn't arbitrary — smaller chunks lose context, larger chunks dilute relevance. Getting this right made a measurable difference in response quality.
  • WhatsApp is infrastructure, not a channel. For Indian businesses, WhatsApp is the CRM. Building natively on top of it — not just adding it as a feature — is the only way to build something people actually use.
  • LangGraph forces you to think in states, not functions. Switching from sequential LangChain calls to a proper state machine changed how we reasoned about the AI pipeline — and made debugging dramatically easier.
  • Voice UX is unforgiving. A 2-second pause in a phone call feels like an eternity. Optimising VAPI response latency taught us more about real-time systems than months of backend work.
  • Agentic systems need guardrails from day one. An AI that can send WhatsApp messages and make phone calls to real people needs careful prompt design and fallback handling — we learned this the hard way during early testing.

What's Next for OutreachX

Short-term

  • [ ] Production WhatsApp Business API (verified business account, unrestricted messaging)
  • [ ] Campaign scheduling — queue campaigns for optimal send times
  • [ ] A/B testing for campaign descriptions and tones
  • [ ] Contact segmentation and tagging

Medium-term

  • [ ] CRM integrations — HubSpot, Zoho, Salesforce
  • [ ] Instagram DM and Telegram channel support
  • [ ] Deeper analytics — conversion tracking, reply sentiment analysis, funnel visualisation
  • [ ] Team collaboration — multiple agents managing the same inbox

Long-term vision

  • [ ] OutreachX as an API — let any SaaS embed AI outreach into their product
  • [ ] Become the default AI outreach layer for Indian businesses — the "Salesforce for Bharat"
  • [ ] Vertical-specific templates: real estate, D2C, edtech, healthcare, financial services

The goal isn't to be another marketing tool. It's to give every Indian business — from a 2-person startup in Patna to a 200-person team in Pune — the same outreach intelligence that enterprise companies pay crores for.

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