AI Customer Support Platform
An enterprise AI customer support platform powered by RAG architecture and AI tools.
Project Architecture & Concept
Launching SoonAI Customer Support Platform is a multi-tenant SaaS developed internally by Sapadiya Software. The platform leverages Retrieval-Augmented Generation (RAG) to scan knowledge documents, auto-respond to customer tickets, and trigger live human handovers. Features a customized floating chat widget compatible with any website.
Main Objective
Create a complete digital ecosystem that makes interaction engaging, secure, and accessible.
Target & Value
Engineered precisely to solve security, caching and database sync problems for active product platforms worldwide.
The Challenges Faced
Every system is plagued by friction before optimization. Here is what we set out to solve.
High Support Ticket Overhead
Customer support desks spending hours resolving repetitive FAQ queries manually.
Inaccurate Bot Answers
Legacy chatbots hallucinating answers and frustrating site visitors.
No Data Ingestion Flow
Lack of workflow systems to parse document updates and sync bot context maps.
How Sapadiya Software Solved It
Our approach blends modular code construction, edge database optimization, and premium, lightning-fast interfaces.
RAG & Vector Embeddings
Chunk support files and index them in PgVector database to retrieve accurate answers.
Hallucination Guards
Programmed strict prompt constraints and temperature thresholds preventing false answers.
Automated Document Parser
Created PDF, markdown, and URL parsing workers that update context index queues.
- High Performance CoreEdge execution paths deployed globally, yielding sub-50ms TTFB.
- Atomic Sync PipelineDual-channel state management with queue triggers to prevent database deadlock states.
- Cryptographic SandboxingAuthenticated access paths and policy layers securing user database vectors.
Key Features
We engineered modules with precision focus on speed, responsiveness, and clean interactive loops.
AI Chatbot
RAG chatbot answering site visitors with 95% response accuracy.
Website Widget
Lightweight floating JS script snippet that embeds in any HTML page.
Human Handover
Seamless chat forwarding to active human agents via Slack hooks.
Conversation Analytics
Analytical dashboard detailing ticket deflections and resolving latency.
Screenshots & Designs
Displaying coming soon wireframes. Core modules are under final RAG prompt validations.
Vector Index Manager
Ingestion dashboard displaying file parsing lists and vectors counts.
Technology Stack
We leverage modern tools to ensure speed, security, and infinite horizontal scalability.
Frontend Engine
- Next.jsProduction
- ReactProduction
- TypeScriptProduction
- Tailwind CSSProduction
Backend Architecture
- Node.jsProduction
- ExpressProduction
- SupabaseProduction
- PostgreSQL (PgVector)Production
Infra & Pipeline
- OpenAI EmbeddingsProduction
- Vercel EdgeProduction
- PineconeProduction
Development Timeline
We execute project cycles logically to prevent scope creep and guarantee on-time shipping.
Discovery
Analyzed vector search requirements and mapped client dashboard requirements.
Design
Styled modern SaaS layouts with dark gradients, micro-animations, and clean panels.
Development
Programmed chunking workers, vector indexing rules, and Slack routing sockets.
Testing
Evaluated prompt iterations to verify response reliability and script load times.
Deployment
Deploying production pipelines to Vercel with database replication rules.
Support
Formulating model updates and fine-tuning ingestion speed.
Project Results
Key performance data points confirming developer expertise and product optimization quality.
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