We rebuild the Data/AI Platform capabilities your team actually uses — purpose-built with agentic AI, hosted in your AWS environment, fully under your control.
Interactive Cost Calculator
Save $3,226,599 over 5 years
Based on build estimate of $350K–$700K
Current Cost with Databricks
- Annual license$510,000
- Implementation (Year 1)$1,275,000
- Annual maintenance$91,800
- Annual integration$75,000
- Annual escalation rate9%
- 5-year projected total$5,251,599
Moonshot Alternative
- One-time build$350K–$700K
- Annual AWS hosting$180,000
- Annual AgentOps$120,000
- 5-year projected total$2,025,000
What You're Really Paying For
| Feature | Used by Most Teams? | Agent-Replaceable? |
|---|---|---|
| Data Engineering | ||
| Data Warehousing | ||
| Machine Learning | ||
| Delta Lake | ||
| SQL Analytics | ||
| MLflow | ||
| Unity Catalog | ||
| Mosaic AI |
Most enterprises use 4 of 8 features but pay for all of them.
What We Build Instead
Data Pipeline Agent
Builds and manages data pipelines with Delta Lake integration and scheduling
ML Training Agent
Orchestrates model training, hyperparameter tuning, and experiment tracking
Data Quality Agent
Monitors data quality, enforces schema validation, and detects drift
SQL Analytics Agent
Executes analytical queries, generates reports, and optimizes query performance
Model Monitoring Agent
Tracks model performance in production, detects degradation, and triggers retraining
Built on AWS
Key Differentiators
- Runs in your VPC — no shared tenancy
- Data stays in your environment at all times
- Full audit trail for every agent action
- Policy-as-code governance and compliance controls
TCO Comparison at 1,000 Users
| Databricks | Moonshot | |
|---|---|---|
| Year 1 Total | $3.8M | $825K |
| 3-Year Total | $6.7M | $1.4M |
| 5-Year Total | $10.2M | $2.0M |
| Ownership | Vendor-owned | You own it |
| Runs in Your VPC | No | Yes |
| Annual Price Increases | 9%+ | $0 |
| Customization | Limited / expensive | Unlimited |
| Compliance | Vendor-dependent | Your controls |
| Exit Cost | High | $0 |
Migration Timeline
Discovery
Audit current usage, integrations, and data flows. Identify the features your teams actually use.
Design
Architect the agentic replacement. Define agent boundaries, data models, and AWS services.
Build
Develop, integrate, and iterate on the purpose-built solution in your AWS environment.
Test & Cutover
Parallel run, data migration, user acceptance testing, and production cutover.
AgentOps
Continuous monitoring, optimization, and evolution of your agentic applications.