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Social Media Auto-Reply

Software & SaaS
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Software & SaaS

Social Media Auto-Reply

Brands receive far more messages and comments than a social team can answer well. RemSoft.Dev designed and built an automated reply system for private messages and comments across Facebook, Instagram and TikTok. It uses retrieval-augmented generation (RAG) to fetch the relevant brand context - products, policies, tone - before generating a response, so replies are accurate and on-voice rather than generic. A unified abstraction layer supports multiple AI providers (Claude, GPT and others), making it straightforward to switch providers or route by cost. Delivered as a production system integrated with the Facebook Graph, Instagram and TikTok APIs and a vector database - not a prompt experiment.

RAGSocial mediaAutomationLLM

Key Challenges

Client: Brand / social-media operator

Channels: Facebook, Instagram, TikTok - DMs and comments

Stack: RAG, vector DB, LangChain, Claude & OpenAI APIs

Design: Provider-agnostic abstraction layer

The project faced several key challenges:

  • Accuracy over fluency: A confident wrong answer damages a brand. Retrieval grounds every reply in real brand content.
  • Three platforms, three APIs: Graph API, Instagram API and TikTok API each behave differently; the system normalises them behind one pipeline.
  • Provider independence: Model prices and quality shift monthly - the abstraction layer keeps switching cheap.

Results

  • Auto-replies on FB, IG and TikTok
  • RAG-grounded, brand-consistent answers
  • Multi-provider LLM abstraction
  • Production integration with platform APIs

3 platforms

handled by one reply pipeline.

RAG

brand context retrieved before every answer.

Multi-provider

Claude, GPT and others behind one interface.

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