Custom AI That Thinks
From fine-tuned LLMs to production ML pipelines — we build intelligent systems that process, learn, and evolve with your data.
Machine Learning Capabilities
Custom Model Training
Purpose-built neural networks trained on your proprietary data for classification, regression, and prediction tasks.
- Proprietary data training
- Custom architecture design
- Hyperparameter tuning
- Model versioning
LLM Fine-tuning
Domain-specific language models adapted for your use case — from legal documents to technical support.
- Domain adaptation
- Instruction tuning
- RLHF & alignment
- Deployment optimization
ML Pipeline Architecture
End-to-end MLOps with automated training, evaluation, and deployment — from data to production.
- Data pipelines
- Automated retraining
- Model registry
- CI/CD for ML
Computer Vision
Object detection, image classification, and visual inspection systems for manufacturing and quality control.
- Object detection
- Image classification
- Visual inspection
- Real-time inference
NLP & Text Analytics
Sentiment analysis, entity extraction, document understanding, and custom text classification models.
- Sentiment analysis
- Entity extraction
- Document understanding
- Text classification
Enterprise Integration
Seamless deployment into existing infrastructure with monitoring, logging, and scalable inference APIs.
- API deployment
- Monitoring & alerting
- Infrastructure integration
- SLA compliance
How We Build Your ML System
Data Audit
We assess your data quality, volume, and availability to determine feasibility and define success metrics.
Architecture
We design the model architecture and pipeline structure aligned with your infrastructure and goals.
Training
Iterative model development with experiments, validation, and performance benchmarking.
Deployment
Production deployment with MLOps workflows, monitoring, and ongoing optimization.
Investment Options
Transparent pricing for ML projects
POC
Proof of concept
- Feasibility study
- Prototype model
- Performance report
- Production roadmap
- 4-6 weeks delivery
Production
Full deployment
- Production-grade model
- MLOps pipeline
- API deployment
- Monitoring setup
- Documentation
- 8-16 weeks delivery
Ongoing
Maintenance & iteration
- Model retraining
- Performance monitoring
- Drift detection
- Dedicated support
- Continuous improvement
- SLA guarantee