Automate, Deploy & Scale Your RAG & ML Models with Confidence
Bridge the gap between AI experimentation and real business impact.
Our LLMOps & AI services help you operationalize AI at scale — ensuring faster deployment, reliable monitoring, and measurable ROI across your data ecosystem.
From Experiments to Impact: Why You Need MLOps & LLMOps?
Modern enterprises are investing heavily in AI — but most struggle to operationalize their ML and LLM models beyond experimentation.
Our solutions address the key challenges that stall your machine learning success:
Weak Observability & Evaluation
Lack of real-time evaluation, metric tracking, and feedback loops makes it hard to detect issues early or measure performance consistently
No Centralized Monitoring
Limited visibility into accuracy, drift, and performance.
Fragmented Workflows
Data science, engineering, and DevOps teams work in silos.
Lack of Governance
Missing version control and audit trails risk compliance breaches.
Slow & Manual Model Deployment
Inefficient handoffs delay insights and business impact.
Observability & Evaluation in MLOps and LLMOps
In modern AI systems, observability and evaluation are the backbone of trust, performance, and continuous improvement.
At DataOptix, we help you monitor, measure, and optimize every model in real time — ensuring consistent results and business alignment.
Comprehensive Performance Tracking
Monitor key metrics such as accuracy, drift, latency, token usage, and response quality for both ML and LLM models.
Prompt & Model Drift Detection
Detect degradation in LLM responses or ML predictions early through dynamic feedback loops and trigger automated retraining.
Human-in-the-Loop Validation
Combine automated scoring with expert review workflows to ensure your models remain accurate, relevant, and ethically aligned.
Our MLOps & LLMOps Solutions
We deliver end-to-end automation, observability, and governance – ensuring every model moves seamlessly from development to deployment to continuous improvement.
End-to-End AI Automation
Automate the complete lifecycle of ML and LLM models — from data ingestion and feature engineering to training, fine-tuning, and deployment — using CI/CD-enabled workflows for rapid iteration.
Real-Time Monitoring & Optimization
Continuously monitor model health across inference, latency, and prompt performance. Automatically trigger retraining or fine-tuning workflows when deviations occur to sustain accuracy and relevance.
Scalable Cloud Infrastructure
Deploy on GCP, AWS, or hybrid environments using Kubernetes, Kubeflow, and Vertex AI for flexible scaling. Our orchestration frameworks efficiently manage both ML pipelines and LLM workloads across distributed compute environments.
Cost-Optimized AI Operations
Minimize operational costs with GPU-aware scheduling, auto-scaling infrastructure, and optimized storage management — ensuring high availability without overspending.
Our Tech Stack: Built for Automation, Scalability, and Reliability
We leverage a modern AI operations stack that supports everything from traditional ML workflows to large language model deployment, fine-tuning, and observability.
MLflow
Kubeflow
Vertex AI
SageMaker
LangChain
LangGraph
Airflow
Github Actions
n8n
Vertex AI Pipelines
Docker
Kubernetes
Terraform
GCP
AWS
Azure
Prometheus
Grafana
LangSmith
Vertex AI Model Monitoring
ChromaDB
Pinecone
Weaviate
Qdrant
Business Impact You’ll Achieve
Unlock the full potential of your AI investments with measurable, long-term business outcomes that drive performance and efficiency.
- Accelerated Go-to-Market: Launch ML-driven products and features up to 50% faster with automated deployment pipelines.
- Consistent Model Accuracy: Maintain optimal performance through continuous monitoring, drift detection, and automated retraining.
- Seamless Team Collaboration: Enable unified workflows between data science, engineering, and DevOps for faster iteration and delivery.
- Optimized Cloud Efficiency: Reduce infrastructure costs by up to 40% through intelligent resource allocation and workload scaling.
- Governance & Compliance Confidence: Ensure full transparency, version control, and security across every stage of your ML lifecycle.
Accelerate Your AI Transformation
Partner with DataOptix to build scalable, secure, and cost-efficient MLOps architectures that keep your models performing — and your business growing.