AI Model Optimization & Tuning for Production

We deliver vertical-specific model fine-tuning and performance optimization for healthcare, financial services, and legal applications. From RAG system implementation to prompt engineering and evaluation harness development, we ensure your AI models achieve production reliability with measurable quality metrics.

MODEL OPTIMIZATION SERVICES

End-to-end AI model optimization from fine-tuning to production evaluation pipelines.

OUR OPTIMIZATION APPROACH

Iterative optimization with continuous evaluation gates ensuring production reliability. 

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        flowchart LR
            subgraph Phase1["Baseline"]
                B1[Data Audit]
                B2[Golden Dataset]
                B3[Baseline Metrics]
            end
            
            subgraph Phase2["Optimization"]
                O1[Prompt Engineering]
                O2[RAG Tuning]
                O3[Fine-tuning]
            end
            
            subgraph Phase3["Evaluation"]
                E1[RAGAS Metrics]
                E2[Regression Tests]
                E3[Quality Gate]
            end
            
            subgraph Phase4["Production"]
                P1[CI/CD Integration]
                P2[Canary Deploy]
                P3[Monitoring]
            end
            
            Phase1 --> Phase2
            Phase2 --> Phase3
            Phase3 -->|Pass| Phase4
            Phase3 -->|Fail| Phase2

1. Baseline Assessment

Comprehensive evaluation of current model performance against your use case requirements. Golden dataset development with domain-specific test cases. Baseline metrics establishment for accuracy, latency, and cost.

2. Optimization Iteration

Systematic experimentation with prompt engineering, retrieval tuning, and model selection. A/B testing framework for comparing configurations. Fine-tuning when base model adaptation is required. Continuous evaluation against golden datasets.

3. Production Hardening

Evaluation harness integration into CI/CD pipelines. Canary deployment with automatic rollback on quality regression. Monitoring dashboards with SLO enforcement. Runbook development for incident response.

Vertical Expertise

Healthcare AI

Medical LLM fine-tuning for clinical decision support. HIPAA-aware training data handling. Human-in-the-loop workflows for high-stakes outputs. Bias testing for demographic fairness. Hallucination prevention for medical accuracy.

Financial Services AI

Compliance-aware models for regulatory mapping and risk assessment. Explainable outputs for Consumer Duty requirements. Audit trail integration for model decisions. Bias monitoring for fair lending and underwriting.

Legal Tech AI

Contract analysis and document processing optimization. Jurisdiction-specific model tuning. Citation accuracy and hallucination prevention. Privilege-aware RAG with access controls. Legal reasoning chain validation.

Evaluation & Quality Assurance

Comprehensive AI quality assurance with production-grade evaluation frameworks: 

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        flowchart LR
            subgraph Inputs["Test Data"]
                GD[Golden Datasets]
                PL[Production Logs]
            end
            
            subgraph Harness["Evaluation Harness"]
                subgraph Tests["Test Suites"]
                    AT[Accuracy Tests]
                    ST[Safety Tests]
                    RT[RAG Metrics]
                end
                
                subgraph RAGAS["RAGAS Evaluation"]
                    F[Faithfulness]
                    AR[Answer Relevance]
                    CP[Context Precision]
                end
            end
            
            subgraph Monitoring["Continuous Monitoring"]
                DD[Drift Detection]
                QA[Quality Alerts]
                RB[Auto Rollback]
            end
            
            GD --> Tests
            PL --> DD
            Tests --> RAGAS
            RAGAS --> DD
            DD --> QA
            QA --> RB

RAG Evaluation (RAGAS)

Faithfulness scoring to measure grounding in retrieved context. Answer relevance assessment. Context precision and recall metrics. Continuous evaluation with drift detection and alerting.

Accuracy Testing

Golden dataset development with domain expert curation. Task-specific evaluation suites. Automated regression testing in CI/CD. Performance benchmarking across model versions.

Safety & Security Testing

Prompt injection attack testing. Jailbreak attempt validation. Output filtering verification. Bias assessment and fairness testing. PII leakage detection.

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Send us a message or schedule a call