Case Studies

Real Systems. Measurable Outcomes.

No demos. No slide decks. These are shipped systems built to remove bottlenecks, protect data, automate work, and support real users.

Laiwyer

Laiwyer case study

The Problem

Legal teams needed complex research across statutes, case law, and internal documents without unreliable answers or missing citations.

What We Built

Built an agentic legal intelligence platform using LangGraph for query planning, tool usage, retrieval, and citation-grounded response synthesis over multi-source legal data.

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Before

Manual legal research, scattered documents, limited citation confidence

After

Agentic research workflows with grounded retrieval and secure workspaces

RAG

Legal retrieval

Cites

Grounded answers

RBAC

Secure access

Stack

LangGraphRAGVector SearchRBACStreaming Chat
TripTalk

TripTalk case study

The Problem

Travelers needed personalized, reliable trip planning instead of piecing together itineraries from scattered blogs, maps, and flight sites.

What We Built

Built an AI travel planning platform with a RAG assistant grounded in Drew Binsky's travel content, plus Google Maps and flight-search MCP integrations for contextual itineraries with real-time flights and destination insights.

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Before

Manual trip research across blogs, maps, and flight sites with generic, ungrounded suggestions

After

AI itineraries grounded in real travel content with live flights, maps, and booking links

RAG

Grounded itineraries

Maps

Destination insights

Flights

Live pricing

Stack

Next.jsFastAPISupabaseOpenAIRAG
ChattyBook

ChattyBook case study

The Problem

Authors needed a platform that could sell books, split revenue across authors, co-authors, and affiliates, and let readers interact with books through AI.

What We Built

Built an AI-powered e-book platform with Stripe Connect revenue distribution, webhook-driven payouts, ElevenLabs voice reading, and a RAG pipeline for chatting with book content.

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Before

Manual revenue handling, limited reader engagement, no AI book interaction

After

Automated payouts, AI voice reading, and book-aware chat experience

AI

Book chat

Multi

Party payouts

Voice

Reading system

Stack

Next.jsStripe ConnectElevenLabsRAGVector Search
Voice Receptionist

Voice Receptionist case study

The Problem

Service businesses were missing inbound calls after hours and losing qualified leads before anyone on the team could respond.

What We Built

Built a voice AI receptionist that answers calls 24/7, qualifies intent, captures contact details, routes urgent requests, and books appointments into the business workflow.

Before

Missed calls, delayed callbacks, manual qualification, and lost demand

After

Every inbound call answered, qualified, logged, and routed automatically

24/7

Call coverage

0

Missed leads

CRM

Lead sync

Stack

VapiOpenAITwilioCRM SyncAutomation

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