Corporate AI Agency & Cognitive Enterprise Pipelines
Custom LLM Fine-Tuning, RAG Architecture & Enterprise AI Automation
Agency33's corporate AI agency engineers secure, private artificial intelligence pipelines for enterprise organizations. We specialize in Retrieval-Augmented Generation (RAG) connecting OpenAI, Claude, and open-source models (Llama 3) to proprietary knowledge bases, vector databases (Pinecone, Qdrant), and secure internal ERP/CRM systems with strict data sovereignty.
Your company wants to leverage generative AI but fears data leaks, inaccurate hallucinations, and security vulnerabilities associated with unvetted consumer tools.
Private enterprise AI infrastructure: we deploy zero-data-retention RAG pipelines that ground AI models exclusively in your verified company documents, delivering pinpoint accuracy with enterprise security.
- Custom enterprise RAG pipeline connecting company documents to vector databases
- Integration of state-of-the-art models (OpenAI GPT-4o, Claude 3.5 Sonnet, or self-hosted Llama 3)
- Vector search setup with Pinecone or Qdrant for semantic document retrieval
- Private web chat interface and WhatsApp/Slack internal assistant integration
- Strict data privacy, encryption, and role-based access control (RBAC) implementation
- Comprehensive AI governance, prompt engineering documentation, and training
Frequently Asked Questions
How do you ensure our private company data is never used to train public AI models?
We utilize enterprise API endpoints with zero-data-retention agreements explicitly forbidding public model training. For highly sensitive data, we deploy self-hosted open-source models (such as Llama 3) within your private cloud VPC.
What is RAG (Retrieval-Augmented Generation) and why does it prevent hallucinations?
RAG searches your verified corporate documents for exact context before generating an answer. If the answer is not present in your official knowledge base, the model explicitly acknowledges it rather than making up false information.
What file formats and systems can your enterprise AI connect to?
We can ingest PDFs, Word docs, spreadsheets, Notion workspaces, Confluence pages, SQL databases, CRM records, and live APIs, updating the vector index automatically as documents change.
Can the AI perform actions, such as updating our CRM or sending emails?
Yes. Through Function Calling and AI Agent frameworks, the model can execute defined actions like booking appointments, querying database records, or drafting proposals with human-in-the-loop approval.