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

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
Tintrust

The Problem

Enterprise teams needed to analyze sensitive data while protecting privacy, preserving compliance, and keeping dashboards fast and usable.

What We Built

Developed a secure data visualization platform with masking, real-time dashboards, Dockerized services, and machine learning based data quality scoring.

Before

Sensitive data workflows were hard to analyze safely at enterprise scale

After

Privacy-safe analytics with masking, dashboards, and quality scoring

Mask

Data privacy

ML

Quality scoring

Live

Dashboards

Stack

ReactTypeScriptFastAPIFlaskDocker
ChattyBook

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.

View live project

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

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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