Proven Results

Case Studies

Real projects with measurable outcomes. We build AI systems that work in production — not just in demos. Here's the proof.

Financial Services12 weeksCase Study #1

AI-Powered Document Processing for a Fintech Platform

85%

Automation rate

18x

Faster processing

94%

Extraction accuracy

$1.2M

Annual savings

Challenge

A fast-growing fintech platform processing thousands of loan applications daily was bottlenecked by manual document review. Compliance officers spent 45+ minutes per application verifying identity documents, income statements, and regulatory forms — leading to 3-day average processing times and growing customer churn..

Solution

We designed and deployed a multi-model AI pipeline combining OCR, LLM-based extraction, and rule-based validation. The system automatically classifies incoming documents, extracts structured data (names, amounts, dates, account numbers), cross-references against compliance rules, and flags exceptions for human review. A RAG layer provides auditors with instant access to relevant regulatory guidance.

Results

The platform now processes 85% of applications without human intervention. Average processing time dropped from 3 days to 4 hours. The compliance team shifted from manual data entry to exception handling and quality oversight, improving both throughput and accuracy.

GPT-4oCustom OCR pipelineRAG with PineconePythonFastAPIPostgreSQL

"Crazy Unicorns didn't just build us an AI tool — they re-engineered our entire document workflow. The accuracy exceeded our expectations, and the system paid for itself within the first quarter."

— VP of Operations, Series B Fintech Company

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E-Commerce & Retail10 weeksCase Study #2

Autonomous Customer Support Agent for E-Commerce

72%

Tickets resolved autonomously

<30s

First response time

4.4/5

CSAT score (was 3.6)

40%

Support cost reduction

Challenge

A direct-to-consumer brand with 200K+ monthly orders was struggling with customer support scalability. Their team of 15 agents handled 4,000+ tickets weekly across email, chat, and social media. Response times averaged 8 hours, CSAT scores were declining, and hiring more agents wasn't economically viable during seasonal peaks.

Solution

We built an autonomous AI support agent powered by a fine-tuned LLM with access to order management, shipping, and product knowledge bases. The agent handles order status inquiries, returns/exchanges, product questions, and shipping issues end-to-end — including executing actions like initiating refunds and updating shipping addresses via API integrations. Complex cases are escalated to human agents with full context.

Results

The AI agent now resolves 72% of support tickets autonomously. Average first response time dropped from 8 hours to under 30 seconds. CSAT scores improved from 3.

Fine-tuned LLMTool-calling agentsShopify APIZendesk integrationNode.jsRedis

"The AI agent handles the majority of our support volume with quality that matches our best human agents. Our team can finally focus on the complex cases that actually need a human touch."

— Head of Customer Experience, D2C E-Commerce Brand

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Manufacturing & Industrial16 weeksCase Study #3

Enterprise Knowledge Management System with RAG

91%

Answer relevance

75x

Faster information retrieval

12K+

Daily queries served

40%

Faster onboarding

Challenge

A Fortune 500 manufacturer with 50,000+ employees across 30 countries had critical knowledge scattered across SharePoint, Confluence, legacy intranets, and thousands of PDF manuals. Engineers spent an average of 2.5 hours per day searching for technical documentation.

Solution

We designed an enterprise RAG system that ingests, indexes, and serves knowledge from 15+ data sources. The system uses hybrid search (semantic + keyword) with domain-specific embeddings fine-tuned on manufacturing terminology. Access controls mirror the existing LDAP/AD structure, ensuring data governance.

Results

Engineers now find answers in under 2 minutes instead of 2.5 hours. New employee ramp-up time decreased from 6 months to 10 weeks.

Custom embeddingsHybrid search (Weaviate)Azure OpenAILDAP/AD integrationReactPython

"This system transformed how our engineers access knowledge. What used to take hours of searching through manuals now takes seconds. It's become the most-used internal tool across all our facilities."

— CTO, Fortune 500 Manufacturing Company

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