From Strategy to Production AI
End-to-end AI and data solutions. We help you build the strategy, design the data platforms, and deploy production ML systems that deliver measurable business value.
AI Strategy & Roadmap
Identify high-value AI use cases, select the right models, and build an implementation plan your team can actually execute
Strategic Planning
Identify high-value AI use cases and prioritize initiatives based on impact and feasibility. Build comprehensive roadmaps that align with your business goals.
- Business capability assessment and use case identification
- ROI analysis and prioritization framework
- Multi-phase implementation planning
- Risk assessment and mitigation strategies
Model Selection
Evaluate AI models from OpenAI, Anthropic, open-source alternatives, and custom solutions. Select the right fit based on your requirements and constraints.
- LLM evaluation (GPT, Claude, Llama, Mistral)
- Cost/performance optimization analysis
- Fine-tuning vs prompt engineering strategy
- Custom model development assessment
Data Platform Design
Build cloud-native data platforms on Snowflake, BigQuery, Databricks, and more, designed for both analytics and ML workloads
Cloud Data Warehouses
Build scalable data warehouse architectures on modern cloud platforms. Design for performance, cost efficiency, and analytical workloads.
- Cloud data warehouse architecture (Snowflake, BigQuery, Redshift)
- Schema design and data modeling best practices
- Query optimization and performance tuning
- Cost monitoring and resource optimization
Data Lakes & Lakehouses
Implement data lakes and lakehouse architectures that unify structured and unstructured data. Enable both analytics and ML workloads on a single platform.
- Data lake and lakehouse implementation (Databricks, Delta Lake)
- Real-time streaming architectures (Kafka, Kinesis)
- Data mesh and decentralized architecture design
- Object storage optimization and partitioning strategies
ML Infrastructure & Pipelines
Deploy MLOps platforms, automated training pipelines, and reliable ETL/ELT workflows that keep models accurate and data consistent at scale
MLOps Platforms
Implement MLOps platforms for automated model training, deployment, and monitoring. Establish CI/CD pipelines for machine learning workflows.
- MLOps platform setup (MLflow, Kubeflow, SageMaker)
- Model training and deployment pipelines
- Experiment tracking and model versioning
- Automated retraining and deployment workflows
ETL/ELT Pipelines
Build reliable data pipelines that extract, transform, and load data at scale. Ensure data quality and consistency across your data ecosystem.
- ETL/ELT pipeline development (Airflow, dbt, Fivetran)
- Data transformation and business logic implementation
- Data quality and validation frameworks
- Data orchestration and workflow automation
Analytics & Governance
Implement BI platforms like Tableau, Power BI, and Looker alongside data governance frameworks that make your data trustworthy for auditors and analysts alike
Business Intelligence
Implement BI platforms that empower business users to explore data and create insights. Design semantic layers and data models for self-service analytics.
- BI platform implementation (Tableau, Power BI, Looker)
- Semantic layer and metrics framework design
- Dashboard and report development
- User training and adoption programs
Data Governance
Establish data governance frameworks that ensure data quality, security, and compliance. Implement policies and tools for responsible data management.
- Data catalog and metadata management
- Data governance policies and compliance frameworks
- Access control and data lineage tracking
- Data privacy and security compliance
Fast-Track Your AI Implementation
Our AI QuickLaunch package turns your strategy into a production-ready MVP in 4-6 weeks.
AI QuickLaunch
4-6 weeks delivery
Production-ready AI MVP with full deployment, training, and ongoing support
Discovery & Planning
- Rapid Discovery Workshop
- Use Case Validation
- AI/ML Architecture Blueprint
Development & Delivery
- Custom AI/ML Implementation
- Cloud Deployment (AWS, GCP, Azure)
- Operational Runbooks
Knowledge Transfer
- Team Training Sessions
- Technical Documentation
- Complete Code Handoff
Post-Launch
- 30-Day Support Window
- Bug Fixes & Refinements
- Production Monitoring Setup
Built and Shipped in Production
Recent AI and data engagements with measurable outcomes.
Enterprise Data Retrieval
Built a retrieval system that gives knowledge workers grounded answers from internal data.
Read case study ML EngineeringLLM Benchmarking Platform
Stood up an evaluation harness so the team could pick the right model with evidence.
Read case study Predictive MLAviation Safety Prediction
Trained a predictive model that flags safety risks earlier in the operational cycle.
Read case studyIndustry Specializations
AI and data solutions tailored to the compliance requirements, data environments, and use cases of your industry.
Healthcare
HIPAA-compliant AI, clinical NLP, EHR integration, and predictive analytics for hospitals and payers.
Financial Services
Fraud detection ML, SR 11-7 model governance, regulatory reporting automation for banks and fintechs.
Public Sector
FedRAMP-authorized data platforms, mission analytics, citizen services AI, and ATO-ready architecture.
Manufacturing
Predictive maintenance, quality ML, supply chain analytics, and OT/IT data integration for manufacturers.
Client Voice
“We had spent a year on AI proofs of concept that never went anywhere. Their team shipped a production system in six weeks that handles thousands of submissions a month.”
Scope a data and ML pilot.
Bring us a use case. We will define the data, the model approach, and a working prototype path you can ship in weeks.