Key Capabilities
Everything you need to build production-grade solutions
AI System Architecture
Design scalable AI architectures covering data ingestion, model serving, APIs, and application integration.
Model Development & Integration
Develop and integrate ML and LLM models into products, platforms, and internal systems.
Data Pipelines & Feature Engineering
Build reliable pipelines for data collection, preprocessing, labeling, and feature generation.
MLOps & LLMOps
Implement CI/CD for models, automated evaluation, versioning, monitoring, and rollback strategies.
AI Application Development
Embed AI into web, mobile, and backend systems: from semantic search to personalized recommendations and real-time decision engines.
AI System Monitoring & Optimization
Track model accuracy, latency, cost, drift, and reliability in production environments.
Our Process
A predictable process built for high-quality delivery
System Understanding & Requirements
Understanding product goals, data landscape, and production constraints.
AI Architecture Design
Designing data pipelines, model architecture, and integration strategy.
Development & Integration
Building models, pipelines, APIs, and application integrations.
Monitoring & Continuous Improvement
Deploying with monitoring, evaluation, and optimization systems in place.
Technologies We Use
Production-tested tools and frameworks
Use Cases
Real-world applications we help teams build and scale
Intelligent Search & Recommendations
Hybrid search combining keyword and vector retrieval, with ranking models that learn from user behavior
AI Copilots & Productivity Tools
Domain-specific assistants that accelerate workflows, answer questions from internal knowledge, and automate repetitive tasks
Predictive Analytics & Forecasting
Demand forecasting, churn prediction, and resource optimization models that inform business decisions
Document Processing & Extraction
Automated extraction, classification, and summarization for contracts, invoices, and unstructured data
Fraud Detection & Anomaly Detection
Scoring models that identify suspicious patterns in transactions, logins, and user behavior
Conversational AI & Automation
Customer-facing chatbots and voice agents with context retention and multi-turn dialogue capabilities
Why Choose Procedure for AI Engineering Services
Companies choose Procedure because:
- Strong focus on production AI, not prototypes
- Clear separation of engineering, ops, and governance
- Experience integrating AI into existing systems
- Flexible delivery models for startups and enterprises
- Security, privacy, and compliance embedded into AI lifecycle
Outcomes from recent engagements
Testimonials
Trusted by Engineering Leaders
“What started with one engineer nearly three years ago has grown into a team of five, each fully owning their deliverables. They've taken on critical core roles across teams. We're extremely pleased with the commitment and engagement they bring.”
Why Quality Matters
Poor engineering costs you
Failed AI Projects
Prototypes that never reach production waste time and resources
Data & Privacy Risks
Unsecured AI systems expose sensitive data
Model Drift
Unmonitored models degrade performance over time
High Operating Costs
Inefficient AI systems accumulate unnecessary costs
Premium development is an investment in
Ready to Discuss Your
AI Engineering Services Project?
Share your AI project requirements, from model architecture to MLOps infrastructure. We'll outline a practical path from prototype to production-ready deployment.
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Frequently Asked Questions
AI engineering focuses on building and operating AI systems in production, while consulting focuses on strategy and recommendations. We are engineering-focused.