Deploy AI chatbots grounded in your data
Generic chatbots hallucinate and leak context. Enterprise RAG systems retrieve answers from your approved knowledge base with citations, access controls, and accuracy guardrails your compliance team can trust.
Talk to an ExpertAlgofy builds production RAG chatbots that ingest PDFs, Confluence, SharePoint, databases, and APIs into vector stores with intelligent chunking and retrieval. Deployed on AWS Bedrock, Google Vertex AI, or open-source stacks, your assistant answers from verified sources — not the open internet.
AWS Partner Program Benefits
As an official AWS Partner and North American distributor, we extend partner-only advantages to qualified customers.
- Free POC for selected projects — Qualified engagements can receive a proof-of-concept built at no charge when you partner with us on AWS — we invest upfront so you validate before you commit.
- Access to AWS partner funds — We tap AWS partner funding programs and credits to offset migration, modernization, and AI workload costs that direct customers cannot access on their own.
- Official AWS distributor · North America — Algofy is an authorized AWS distributor in North America, enabling discounted AWS resources and consolidated billing support for enterprise teams.
- Discounted AWS resources — Beyond standard pay-as-you-go pricing, eligible customers receive partner-level discounts on AWS consumption through our distributor relationship.
Built for enterprise outcomes
Accurate, cited answers
Retrieval pipelines that surface source documents with every response, reducing hallucinations and giving users confidence in AI-generated answers.
Enterprise data security
Documents stay in your cloud account. Role-based access ensures users only retrieve content they are authorized to see.
Multi-format ingestion
Process PDFs, Word docs, HTML, spreadsheets, Slack threads, and database records into a unified searchable knowledge base.
Continuous improvement
Feedback loops, retrieval evaluation, and re-indexing pipelines that improve answer quality as your content evolves.
Our proven process
Knowledge audit
Identify document sources, access policies, content freshness requirements, and use cases that define chatbot scope.
Ingestion pipeline
Build document parsers, chunking strategies, embedding models, and vector store architecture tuned to your content types.
RAG orchestration
Configure retrieval queries, reranking, context assembly, and LLM prompting with guardrails for tone, scope, and citation.
Security & access controls
Implement authentication, per-user retrieval filtering, audit logging, and PII detection on inputs and outputs.
Launch & evaluation
Deploy to production with A/B testing, retrieval accuracy benchmarks, and user feedback collection for ongoing tuning.
What you receive
RAG architecture design document
Document ingestion pipeline
Production chatbot application
Access control & audit configuration
Retrieval evaluation report
Common questions
How is RAG different from a standard ChatGPT integration?
RAG retrieves answers from your specific documents before generating a response, with source citations. Standard integrations rely on the model training data, which lacks your internal knowledge and cannot cite proprietary sources.
Where does our data live during RAG deployment?
All documents, embeddings, and vector stores remain in your AWS or Google Cloud account. Algofy builds within your infrastructure boundaries — no data is sent to third-party SaaS platforms.
How do you reduce AI hallucinations?
We use constrained retrieval, source citation requirements, confidence scoring, reranking models, and prompt engineering that instructs the LLM to answer only from retrieved context. Regular evaluation benchmarks track accuracy over time.
Ready to get started?
Talk with our AWS and Google Cloud partner team about your enterprise rag chatbot goals. Qualified AWS engagements may include a free POC, partner funding, and discounted resources.
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