Avix Labs

Case Studies

Real results from real projects. Anonymised client stories covering AI application development, intelligent automation, and enterprise platform engineering.

ManufacturingIntelligent Automation

Invoice Processing Automation

A manufacturing business was processing hundreds of thousands of supplier invoices annually — a slow, labour-intensive, and error-prone process. We built an AI extraction and workflow automation system with full ERP integration.

The Challenge

The client's accounts payable team was manually keying data from supplier invoices into their ERP system — a process that was slow, costly, and prone to errors. With invoice volumes growing year on year, scaling the team was not a viable path. They needed an automated system that could handle varied invoice formats, match against purchase orders, route exceptions for review, and post validated invoices directly to the ERP.

Our Solution

We designed and built an end-to-end intelligent document processing pipeline. AI models extract structured data from any invoice format — PDFs, scanned images, and email attachments. The system validates extracted data against PO records, flags discrepancies, routes exceptions to the appropriate reviewer, and posts approved invoices to the ERP via REST API. The entire workflow is logged with a full audit trail.

Solution Highlights

  • AI-powered extraction from any invoice format — PDFs, images, email attachments
  • Automatic PO matching and 3-way validation (PO, receipt, invoice)
  • Approval routing by value threshold and vendor rules
  • ERP integration via REST API with error handling and retry logic
  • Exception queue with human review workflow and resubmission
  • Full audit trail for every transaction

Results

Processing cycle time reduced significantly. Near-elimination of manual data entry for standard invoices. Documented annual cost savings against previous headcount requirements. The system handles exceptions intelligently, routing only genuinely ambiguous cases to human review — reducing reviewer workload to a fraction of the original volume.

90%+

Manual entry eliminated

↓ Significantly

Processing cycle time

Documented

Annual cost savings

Document AIPythonAWS LambdaREST APIPostgreSQL
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Legal TechnologyAI Application Development

Contract Analysis as a Product Feature

A legal SaaS company needed to add AI-powered contract analysis as a core product feature. We built contract analysis capability using a foundation model fine-tuned for legal reasoning.

The Challenge

A growing legal SaaS platform needed to differentiate in a competitive market by offering AI-native contract review. Their enterprise customers demanded a feature that could automatically extract key clauses, identify risk, and flag non-standard terms — integrated directly into the existing platform rather than as a bolt-on tool. The capability needed to be accurate enough to trust, fast enough for commercial use, and flexible enough to handle diverse contract types.

Our Solution

We designed and integrated a contract analysis engine using a foundation model with legal reasoning capabilities. The system extracts over 50 defined clause types, scores risk against a configurable rubric, highlights non-standard or unusual terms, and compares against the client's standard contract templates. The capability was delivered as an internal REST API integrated into the existing SaaS platform with role-based access control and per-organisation configuration.

Solution Highlights

  • Foundation model integration optimised for legal reasoning and clause extraction
  • Structured extraction of 50+ clause types including payment terms, liability, IP, termination
  • Risk scoring and red-flag identification against configurable rubrics
  • Template comparison: highlights deviations from standard contracts
  • REST API integration with the existing SaaS platform
  • Role-based access and per-organisation configuration

Results

High extraction accuracy across standard commercial contract types. The AI contract analysis feature became the company's primary differentiator in enterprise sales conversations, contributing to multiple new enterprise deals. The system processes contracts in seconds — versus 30–60 minutes of manual review for the same output.

50+

Clause types extracted

Seconds

Review time

Key differentiator

Sales impact

Claude APIPythonFastAPIPostgreSQLAWS ECS
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HealthcareAI Application Development

Clinical Decision Support System

A physician network needed instant access to medical knowledge at the point of care. We built a HIPAA-compliant AI system integrated with their EHR that provides real-time clinical guidance.

The Challenge

Physicians in the network were spending valuable consultation time searching clinical guidelines, drug interaction databases, and treatment protocols across multiple disconnected systems. The client needed a unified AI assistant that could surface relevant clinical knowledge instantly — with full HIPAA compliance, EHR integration, and high enough accuracy to support (not replace) clinical decision-making.

Our Solution

We built a HIPAA-compliant AI knowledge system using a RAG architecture over a curated clinical knowledge base. The system ingests clinical guidelines, formularies, drug interaction data, and institutional protocols. It integrates with the EHR to pull patient context (allergies, current medications, diagnoses) and uses this context to surface relevant, patient-specific clinical information. All queries and responses are logged with full audit capability.

Solution Highlights

  • HIPAA-compliant architecture with data encryption at rest and in transit
  • RAG-based knowledge retrieval over curated clinical guidelines and protocols
  • EHR integration for patient context — allergies, medications, active diagnoses
  • Real-time drug interaction checking against current medications
  • Audit logging of all queries and responses for compliance
  • Role-based access for physicians, nurses, and pharmacists

Results

Improved clinical decision-making speed at point of care. Physicians report faster access to relevant guidelines without switching between systems. The system surfaces patient-specific drug interactions and contraindications that were previously reliant on manual lookup — reducing the risk of oversight in complex cases.

Multiple → 1

Systems consolidated

HIPAA

Compliance

EHR integrated

Context-aware

RAG / pgvectorClaude APIPythonAWSHL7 FHIR
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