AI/ML Services
End-to-end AI/ML engineering services from research to production.
Custom Model Development
Build and train custom ML models tailored to your specific business needs and data.
LLM Integration
Integrate large language models into your applications with proper prompt engineering and fine-tuning.
ML Pipelines
Design and implement end-to-end ML pipelines for data processing, training, and deployment.
Data Engineering
Build robust data infrastructure for collecting, processing, and storing training data.
MLOps
Implement CI/CD for ML models with versioning, testing, and automated deployments.
Model Monitoring
Track model performance, detect drift, and maintain model quality in production.
AI/ML Stack
Technologies and frameworks we work with
Custom AI & ML Systems
We don’t sell generic models. We engineer purpose built AI systems tailored to your business logic, data, and constraints.
Core Capabilities
- Domain-specific ML models
- Hybrid AI systems (rules + ML + LLMs)
- Private and open-weight model deployments
- Multi-model orchestration and routing
Use Cases
- Intelligent recommendations and scoring engines
- Forecasting and optimization systems
- Anomaly and fraud detection
- Decision automation pipelines
LLM & Agent-Based Systems
We design agentic AI systems that reason, plan, and execute across tools, APIs, and data sources, safely.
Capabilities
- LLM-powered agents with tool access
- Multi-agent workflows and orchestration
- Guardrails, constraints, and safety layers
- Memory, retrieval, and reasoning pipelines
Use Cases
- AI copilots for internal teams
- Intelligent automation and workflow agents
- Knowledge assistants over private data
- AI-powered commerce, operations, or support systems
Retrieval-Augmented Generation (RAG)
We build production-grade RAG pipelines, not brittle demos.
RAG Foundations
- Secure document ingestion and indexing
- Vector databases and hybrid search
- Fine-grained access control
- Evaluation, monitoring, and hallucination reduction
Works With
- Internal documents
- Databases and APIs
- Product catalogs
- Regulatory or compliance data
Private AI & Secure Inference
For teams that cannot send data to public AI APIs.
Secure Deployment
- On-prem or private cloud deployments
- Open-weight and fine-tuned models
- Data isolation and tenant separation
- Secure inference pipelines
Ideal For
- Regulated industries
- Enterprise and government
- IP-sensitive platforms
- Long-term cost control
Tools & Frameworks We Use
We select the right stack for your constraints, not a one-size-fits-all vendor.
ML & LLM Frameworks
- PyTorch, TensorFlow, scikit-learn
- Hugging Face Transformers, Sentence Transformers
- LangChain, LlamaIndex
Vector Search & RAG
- Pinecone, Weaviate, Milvus, FAISS
- Postgres + pgvector, Elasticsearch
- OpenSearch, Vespa
MLOps & Serving
- MLflow, Weights & Biases, DVC
- Kubeflow, Ray, Airflow
- Triton Inference Server, vLLM, TorchServe
Infrastructure & Observability
- Kubernetes, Docker, Terraform
- Prometheus, Grafana, OpenTelemetry
- Vault, OPA, Trivy