Case Studies

Results that speak for themselves.

Real projects with verifiable impact metrics.

AI-Powered Due Diligence Automation
Mining / Due DiligenceMining company — USA / LATAM4 months

AI-Powered Due Diligence Automation

85%

Validation time reduction

95%

Classification accuracy

70%

Fewer human errors

Challenge

Mining company with operations across multiple regions needed to verify the identity of 500+ miners using documents (IDs, photos, PDFs) manually — a slow, error-prone process that delayed field personnel onboarding.

Solution

We built an automated due diligence platform where operators upload ZIP files with identity documents. Computer vision agents (Qwen2.5-VL) classify and extract data from each document, a facial recognition module validates photo-to-ID correspondence, and the system generates consolidated XLSX audit-ready reports — all encrypted at rest with Fernet.

Qwen2.5-VL, FastAPI, PostgreSQL, Celery, Redis, Next.js
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B2B Sales Intelligence with AI
Financial Services / B2B SalesEnterprise software company — Global4 months

B2B Sales Intelligence with AI

70%

Research time reduction

3x

More meetings booked

50%

Better conversion

Challenge

Sales team with multi-market presence needed to manually research each prospect account: company profile, key contacts, relevant publications, and personalized email drafting. Each account analysis took 4-6 hours, limiting capacity to ~5 accounts per week per rep.

Solution

We built a sales intelligence platform that automatically generates complete account profiles: company information, opportunity signals, decision-maker identification, media mention analysis, and hyper-personalized email sequences. Multiple AI agents work in parallel with multi-language support, generating executive briefs ready for the rep in under 2 minutes per account.

FastAPI, Azure OpenAI, Perplexity AI, PostgreSQL
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Autonomous Customer Service Agent
Customer ServiceTelecommunications Company — LATAM2 months

Autonomous Customer Service Agent

60%

Ticket reduction

< 3s

Response time

92%

Satisfaction (CSAT)

Challenge

The support team was overwhelmed by repetitive first-level inquiries (such as order status and billing), resulting in response times exceeding 24 hours and low customer satisfaction.

Solution

We developed and integrated an AI agent on WhatsApp using n8n for orchestration. The agent connects to inventory and billing APIs to resolve inquiries autonomously. If it detects frustration through sentiment analysis or encounters a complex query, it hands off the case with full conversation history to a human agent in Slack.

LangGraph, Claude 3.5 Sonnet, n8n, Redis, Slack API
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Intelligent Corporate Document Extraction
Document ManagementLogistics Conglomerate — Colombia3 months

Intelligent Corporate Document Extraction

90%

Administrative time saved

95%

Data accuracy

10s

Processing per page

Challenge

Manually processing and digitizing thousands of invoices and supplier contracts per month consumed significant administrative time, introducing frequent errors in ERP entries and delaying payments.

Solution

We implemented an AI Document Intelligence solution based on advanced OCR and frontier language models. The system classifies the type of document received via email, extracts key fields (amount, issuer, tax ID, due date), and structures them into a JSON format for automatic ERP registration.

FastAPI, Azure Document Intelligence, Python, PostgreSQL
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Autonomous Bank Reconciliation and Accounting
Internal Process AutomationWholesale Distributor — Medellín6 weeks

Autonomous Bank Reconciliation and Accounting

85%

Auto reconciliation

1 day

Monthly accounting close

80%

Fewer entry errors

Challenge

The finance team spent 5 to 7 days a month manually reconciling hundreds of incoming bank transfers against issued invoices due to incomplete or erroneous payment descriptions in bank statements.

Solution

We designed a workflow in n8n that downloads bank statements daily. An AI agent processes confusing descriptions, infers client or supplier identity by cross-referencing historical data, executes the reconciliation in the ERP, and flags critical discrepancies in Slack.

n8n, Python, FastAPI, Slack API, PostgreSQL
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Churn Prediction in Recurring Customers
Analytics & PredictionB2B SaaS Company — Global3 months

Churn Prediction in Recurring Customers

22%

Churn reduction

4.2x

Return on investment (ROI)

90%

Alert accuracy

Challenge

The company experienced silent customer loss. The Customer Success team was unable to identify in advance which accounts were dissatisfied or inactive before they decided to cancel their subscription.

Solution

We built a predictive model that analyzes temporal data on platform usage, support ticket volume, and interaction history. The system calculates a risk score and automatically alerts support with a retention offer drafted by AI.

Python, XGBoost, TimescaleDB, Next.js, FastAPI
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Employee Onboarding & Management Portal
HR & OnboardingEmployee Outsourcing Company — Colombia2 months

Employee Onboarding & Management Portal

80%

HR time saved

4 hours

Onboarding time

95%

Employee satisfaction

Challenge

Rapid headcount growth generated an excessive administrative burden on the HR team, who had to manually collect, verify identity documents, and onboard each new employee, delaying project starts.

Solution

We implemented a virtual assistant that guides new hires through their first 15 days. The AI verifies document validity via computer vision, answers corporate policy questions, and automatically provisions their technical credentials.

Next.js, FastAPI, n8n, OpenAI GPT-4o, AWS S3
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Multimodal Sales Assistant & Personal Shopper
Retail & E-commerceFashion & Home E-commerce — Latam2.5 months

Multimodal Sales Assistant & Personal Shopper

28%

AOV increase

18%

Sales conversion

45%

Fewer empty carts

Challenge

Customers struggled to find products matching their personal style within a very extensive catalog, leading to low conversion rates and abandoned shopping carts.

Solution

We developed a WhatsApp AI agent capable of receiving descriptions and photos from users (e.g., of an outfit or a room to decorate). The agent visually analyzes the images, searches for similar items in the store's vector catalog, and offers personalized recommendations with checkout links.

Gemini 2.0 Flash, FastAPI, Vector Search, Next.js, n8n
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