SERVICE: AI & Machine Learning

AI & Machine Learning

We operationalize AI across the enterprise — from predictive models and LLM-powered applications to agentic workflows and computer vision. Our team turns prototypes into deployment-ready, sustainable AI programs.

Applied ML & Predictive Modeling

We build production-grade machine learning models that solve real business problems — not science experiments. Our expertise spans gradient-boosted ensembles for tabular data, hybrid neural networks like our CANN architecture for insurance pricing, time-series forecasting for demand and revenue planning, and anomaly detection for fraud and risk management. Every model we deliver includes holdout validation, fairness audits, interpretability analysis, and a clear path to production deployment. We specialize in the financial services and insurance domains where model accuracy directly impacts the bottom line.

END-TO-END ML LIFECYCLE — FROM DATA TO PRODUCTIONDATACollectionCleaningLabelingVersioningAugmentationExploratoryAnalysis (EDA)DVC · SparkFEATURESFeature DesignSelectionEncodingNormalizationFeature StoreOnline & OfflineServingFeast · TectonTRAININGModel SelectionHyperparameterTuningCross-ValidationDistributed GPUExperimentTrackingMLflow · W&BEVALUATIONAccuracy MetricsFairness AuditsA/B TestingHoldout ValidationError AnalysisModel RegistryChampion/ChallengerEvidently · Great Ex.DEPLOYMENTModel ServingAPI EndpointsBatch InferenceEdge DeploymentCanary RolloutAuto-ScalingContainerizedK8s · SageMakerMONITORING & MLOPSData Drift DetectionPerformance Degradation AlertsAutomated Retraining TriggersRETRAINCONTINUOUS IMPROVEMENT LOOP — PRODUCTION ML AT SCALE

Agentic AI & LLM Solutions

Large language models are transforming how enterprises process information, interact with customers, and automate knowledge work. We build LLM-powered applications that go beyond simple chatbots — including Retrieval-Augmented Generation (RAG) systems that ground responses in your proprietary data, document AI pipelines that extract and classify information from contracts, claims, and regulatory filings, and agentic workflows that orchestrate multi-step business processes autonomously. Our solutions use fine-tuned models where needed while managing cost, latency, and hallucination risk through careful prompt engineering and guardrail design.

Computer Vision & Specialized AI

Beyond text and tabular data, we develop computer vision models for industries where visual information is critical. This includes claims photo analysis for insurance carriers, document OCR and structured extraction for processing legacy paper records, quality inspection systems for manufacturing, and asset monitoring solutions. We also build multi-modal models that combine vision and language understanding for complex workflows — like analyzing damage photos while cross-referencing policy terms to estimate coverage automatically.

AI CAPABILITIES MAP — MODALITIES & BUSINESS APPLICATIONSLLMs & NLPFine-Tuned LLMsDomain-specificRAG SystemsKnowledge basesDocument AIExtract & classifyContract analysis · Compliance · Customer support · Knowledge mgmtGPT-4 · Claude · Llama · Embeddings · Vector DBsPREDICTIVE MLRisk ScoringCredit / InsuranceForecastingDemand / RevenueAnomaly Det.Fraud / OutliersCredit risk · Claims prediction · Churn · Pricing optimizationXGBoost · Neural nets · CANN hybrids · Time-series · EnsemblesCOMPUTER VISIONDocument OCRStructured extractImage AnalysisClassificationObject DetectionInspection / QCClaims photos · Document digitization · Quality inspection · AssetsVision transformers · YOLO · Custom CNNs · Multi-modal modelsAGENTIC AIWorkflow AgentsMulti-step tasksTool-Using AIAPI orchestrationDecision AgentsAutonomous opsUnderwriting automation · Report gen · Pipeline managementLangChain · CrewAI · Function calling · RAG

Research-to-Production Pipeline

The biggest challenge in enterprise AI is not building models — it is getting them into production reliably. We implement end-to-end MLOps pipelines that cover feature engineering, model training, evaluation, deployment, and continuous monitoring. Our infrastructure handles data drift detection, automated retraining triggers, champion-challenger testing, and canary deployments. We use MLflow, Weights & Biases, and cloud-native ML services to create reproducible experiments and version-controlled model registries. The result is an AI program that improves continuously rather than degrading over time.