Reference Architectures

As a software engineering firm, we lead with logic. These case studies represent our standardized, production-ready frameworks for common business bottlenecks.

Real Estate / Sales

Autonomous Lead Triage Engine

PythonOpenAI APITwilioFastAPI

The Problem

Sales teams lose 50% of conversion potential if a lead isn't contacted within 5 minutes. Most inquiries arrive after-hours and sit in an inbox for 12+ hours.

Technical Logic

A persistent listener script that triggers on new IMAP/SMTP events. It uses an LLM to parse unstructured email text into structured JSON, then routes priority leads via Twilio API.

Result:0-minute response time and 24/7 lead coverage without human intervention.
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Logistics / Finance

AI-Driven Invoice Reconciliation

Vision LLMJSON SchemaNode.jsRegular Expressions

The Problem

Logistics firms handle thousands of subcontractor invoices with varied layouts. Manual data entry into accounting software (e.g., Netvisor) is slow and error-prone.

Technical Logic

A computer vision pipeline using Vision LLMs to extract line items, IBANs, and VAT totals. A secondary validation layer checks IBANs against a whitelist to prevent fraud.

Result:95% reduction in manual data entry and 100% IBAN security verification.
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Internal Operations

RAG Knowledge Base (Technical Docs)

PineconeLangChainSupabaseTypeScript

The Problem

New employees spend 20% of their day searching for information across scattered PDF manuals, Slack threads, and internal Wikis.

Technical Logic

A Retrieval-Augmented Generation (RAG) system. Documents are chunked and stored in a Vector Database. The agent retrieves the most relevant context to answer staff queries accurately.

Result:Immediate access to company knowledge, reducing internal support tickets by 60%.

All architectures are built with a **Security-First** mindset: End-to-end encryption, GDPR-compliant data handling, and zero-trust API access.