PATHSDATA
AWSAWS Select Tier Consulting Partner

Generative AI

Build production-ready AI solutions with Amazon Bedrock

RAG systems, AI agents, and custom LLM applications that deliver real business value — not just demos.

Challenges We Solve

Moving from ChatGPT experiments to production AI is hard. We make it easy.

LLM Hallucinations

Generic AI models give inaccurate answers because they lack your company's specific knowledge and context.

Data Security

Worried about sending sensitive data to third-party AI services and losing control of your information.

Integration Complexity

Struggling to connect AI capabilities with your existing systems, databases, and workflows.

Cost at Scale

Token costs explode as usage grows, making AI initiatives unsustainable without optimization.

What We Build

Enterprise-grade Gen AI solutions powered by Amazon Bedrock.

RAG Systems (Retrieval Augmented Generation)

Ground LLM responses in your company's actual data. Connect to documents, databases, and knowledge bases for accurate, cited answers.

Amazon BedrockOpenSearchPineconeKnowledge BasesS3

AI Agents & Automation

Build autonomous AI agents that can reason, plan, and take actions. Automate complex workflows with multi-step reasoning.

Bedrock AgentsLangChainMCPStep FunctionsLambda

Enterprise Chatbots & Assistants

Deploy intelligent chatbots for customer support, internal help desks, and domain-specific Q&A with proper guardrails.

ClaudeAmazon LexConnectKendraAPI Gateway

Custom LLM Applications

Build bespoke AI applications tailored to your business — from document processing to code generation to creative tools.

Claude 3.5LlamaTitanCohereStability AI

Why Choose PATHSDATA

Grounded Responses

RAG ensures AI answers are based on your actual data, not hallucinations.

Enterprise Security

Your data stays in your AWS account. No third-party API calls with sensitive info.

Production Ready

We build for scale — proper error handling, monitoring, and cost controls.

Domain Expertise

AI that understands your industry terminology and business context.

Popular Use Cases

Customer Support Automation

AI chatbot that resolves 70%+ of support tickets by searching your knowledge base and previous resolutions.

Document Intelligence

Extract insights from contracts, reports, and emails. Summarize, compare, and answer questions about documents.

Code Assistant

Internal copilot trained on your codebase, documentation, and coding standards for faster development.

Sales Intelligence

AI that analyzes calls, emails, and CRM data to surface insights and automate follow-ups.

Technology Stack

Foundation Models

  • Claude 3.5
  • Llama 3
  • Titan
  • Cohere

Vector DB

  • OpenSearch
  • Pinecone
  • pgvector
  • Chroma

Orchestration

  • Bedrock Agents
  • LangChain
  • MCP

AWS Services

  • Bedrock
  • Kendra
  • SageMaker
  • Lambda

Our Process

1

Use Case Discovery

Identify high-impact Gen AI opportunities. Define success metrics and ROI expectations.

2

Data & Architecture

Design RAG architecture, knowledge base structure, and integration points with your systems.

3

Build & Iterate

Develop, test, and refine with real users. Prompt engineering and guardrails optimization.

4

Deploy & Monitor

Production deployment with proper observability, cost tracking, and continuous improvement.

CASE STUDY

Fatevision LLC — Gen AI Astrology Platform

POC delivered in 4 weeks using Amazon Bedrock and RAG for personalized readings.

Read Case Study

Ready to Build Your Gen AI Solution?

Let's discuss how Generative AI can transform your business. Start with a free AWS-funded POC.