Pricing
Pricing plans for teams of all sizes
Initial Big Data Platform Consultation — 1 Hour
Data Strategy Discovery Session - Hour Get clarity on your data challenges and unlock next steps with a focused strategy session. Perfect for scoping new projects or getting expert guidance on your current data road blocks.
- Comprehensive Data Audit & Assessment
- Scalability Planning & Cost Optimization
- Custom Data Architecture Blueprint
- Data Governance & Security Framework
- Implementation Timeline & Milestone Planning
- Actionable next steps roadmap
- Follow-up email summary
Small Business Platform
Get AI-ready insights—without enterprise complexity or cost. This package is designed for small teams that want to activate their data for analytics, ML, and AI—without building an entire data platform from scratch. We connect and curate your data from sales, marketing, and e-commerce systems to create a centralized feature layer—so your KPIs, business metrics, and AI models all use the same trusted data source. You focus on insights. We handle the rest.
- Data Pipeline Engineering – Automated data ingestion and transformation from your tools and apps
- Feature Store Setup – Unified, reusable features for dashboards, ML, and AI workloads
- Cloud Infrastructure Management – Fully managed in your cloud (AWS, GCP, or Azure)
- Our system is cloud-agnostic, meaning it works with whatever tools or cloud provider you already use
- Incident Response & Resolution
- Cloud Infrastructure Management
- Technical Support & Consultation
- 24/7 Pipeline Monitoring & Alerting
Managed Data Platform as Service Standard
Maintain and monitor pipelines (batch, real-time up to 2 pipeline)
- Apply updates and patch cloud/data tooling
- Proactive Maintenance & Optimization
- Automated Security Updates & Patching
- Data Quality Assurance & Validation
- Incident Response & Resolution
- Cloud Infrastructure Management
- Cloud Agnostic Deployment
- Technical Support & Consultation
- 24/7 Pipeline Monitoring & Alerting
Proof of Concept Development
1. Connect to real data sources 2. Define & build one concrete use case 3. Develop minimal frontend / output layer 4. Document and handoff with next steps 5. Includes 1–2 check-in calls
- Connect to real data sources
- Define & build one concrete use case
- Develop minimal frontend / output layer
- Document and handoff with next steps
- End-to-End Use Case Implementation
- Functional Data Pipeline Architecture
- Data Quality & Validation Framework
- Comprehensive Technical Documentation