www.mammothgrowth.com
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Faster delivery, higher quality: data projects completed in days, not months.
Our Agentic Workflow: See Exactly How It Works
✅ Our agentic workflow combines strategic human expertise with AI agents that execute with precision.
✅ Each phase builds on the last, turning your requirements into production-ready data systems faster, and better, than you thought possible.
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Phase 1: From Discovery Call to Requirements
How We Turn Your Words Into Validated Business Documentation
After your discovery session, our business agent transforms your call transcript into a complete business requirements document. But here's where we're different: our consultants don't just review it—they interrogate it.
You get:
  • Goals and business context clearly documented
  • In-scope deliverables vs. out-of-scope (no surprises later)
  • Business rules, edge cases, and impact analysis
  • Risks and blockers surfaced immediately
  • A living document validated by consultants who were in the room with you
Why it matters: Our process captures essential facts, framed with context, from your conversation immediately, then validates it with human expertise. You move forward with confidence, not ambiguity.
Phase 2: From Requirements to Technical Architecture
How We Audit Your Data and Generate Production-Ready Specs
Our ai-data-agent connects directly to your cloud data warehouse, scanning source data for patterns, inconsistencies, duplicates, and quality issues. The insights it uncovers feed directly into the process, enabling the agent to translate your business requirements into a precise technical specification—the blueprint for your data build.
You get:
  • Complete data discovery (ranges, duplicates, missing fields, outliers)
  • Visual flows: bronze → silver → gold layer architecture
  • Schema definitions aligned with your business rules
  • Risks flagged with mitigation strategies
  • A reviewed, implementation-ready tech spec
Why it matters: Great outcomes aren’t luck, they’re designed. Meticulous planning and rigorous standards ensure the first build is the right build. No pitfalls, no costly rework.
Phase 3: From Spec to Production-Grade Code
How We Build Your Entire Data Pipeline
Guided by your technical specification, our ai-data-agent builds production-ready dbt models across bronze, silver, and gold layers—complete with integrated documentation and automated testing.
You get:
  • Normalized bronze models filtering invalid data
  • Business logic applied in silver
  • Gold-tier models delivering executive-ready insights
  • Rich, contextual documentation with inline comments
  • Automated quality checks and dependency validation
  • GitHub pull requests with test results and clear summaries
Why it matters: Every model is documented, tested, and validated before it reaches production.
Real Clients, Real Results
Etsy: Unified SEO Command Center for Massive-Scale Search Data
Challenge: SEO team drowning in siloed data across Google Search Console, Botify, and proprietary log files—trillions of rows with no unified view for strategic decision-decision-making
Result: Delivered 3 months ahead of schedule a comprehensive SEO data platform unifying all sources into a single Looker-based command center with real-time insights
Impact: Eliminated manual data reconciliation across tools. SEO team now has unified visibility into search performance, crawl efficiency, and log-level behavior—enabling data-driven optimization at Etsy's scale
Replit: Automated ARR Forecasting for High-Growth Finance Team
Challenge: Finance team buried in manual revenue reporting—needed automated ARR metrics and foundational data infrastructure to scale with rapid business growth
Result: Complete medallion architecture (bronze/silver/gold) in BigQuery with comprehensive UBB metrics and automated ARR models delivered in 6 weeks
Impact: Manual revenue reporting eliminated. Finance team now has real-time visibility into unit-based billing metrics, ARR drivers, and forecasting capabilities—freeing analysts from spreadsheet work to focus on strategic analysis
Progress: ARR & Enterprise Revenue Recognition Overhaul
Challenge: ARR calculations fragmented across Microsoft SQL Server, Oracle Financial Cloud, and Tableau created inaccurate reporting, inefficient sales workflows, and limited FP&A visibility into revenue drivers.
Result: In just 2 months, Mammoth Growth migrated Progress to Snowflake with a medallion architecture, helper models, dbt semantic layer, and Streamlit prototyping to accelerate validation.
Impact: Embedded ARR metrics directly in Salesforce for sales reps, enabled FP&A drill-down into revenue drivers, and established a scalable foundation for AI and future acquisitions.
Mammoth Growth was able to jump in, evaluate, and deliver accurate user-based-billing metrics across the entire product line within 6 weeks of kicking off!
-Amol Hardikar
CFO, Replit
Mammoth Growth's strategic approach to data architecture has made them invaluable thought partners as we scale our analytics capabilities.
-Anthony Capua
Director, Finance & PS Ops, Progress
Our business is complex, and so is our revenue reporting. Mammoth Growth refactored, improved, and automated our forecasting within weeks!
-Jenny Decker
CFO, Tempo
How We Built AI That Actually Delivers
Our ai-data-agent was engineered with:
A decade of hands-on data consulting experience
900+ projects worth of patterns, edge cases, and best practices.
Laser focus on dbt-native workflows and the modern data stack
Continuous evaluation by onshore elite analytics engineers
The Facts: Numbers Behind Our Agentic Workflow
60x
faster deliverable speed
Our proprietary agents accelerate delivery, dramatically reducing the time it takes to generate a production-ready data deliverable.
95%
completeness in zero-shot scenarios
Our agents create outputs that are ~95% complete from the start. Then our expert team validates, refines, and carries them over the finish line with precision.
3-5x
total output capacity
With the heavy lifting handled by agents, our experts focus on thinking, refining, and polishing. Projects that once took weeks now wrap in days—complete with full documentation and testing.
Schedule your next working session with our team
No pressure. Just a straightforward conversation about how we can help you move faster.
FAQs

How do you maintain quality at 60x speed?

We compare all outputs to proven patterns from our 900+ successful projects. Our agent creates detailed test coverage for every deliverable, analyzes your data to produce comprehensive architectural decision reports, and all outputs are reviewed by our team of experts before delivery. This ensures enterprise-grade quality without sacrificing speed.

What if my data is complex or messy?

Our ai-data-agent is specifically designed to find issues—inconsistencies, duplicates, missing fields, outliers—during the discovery phase. We surface problems in minutes, not weeks into the project. Messy data is expected and handled systematically.

Do I need to use specific tools?

We specialize in Snowflake (or BigQuery) & dbt. If you're using these tools (or planning to), we're an excellent fit.

How involved will my team need to be?

We need you for strategic decisions and requirements validation. Your time commitment is minimal—discovery sessions, specification reviews, and final validation. The heavy technical work happens on our end.

What happens after implementation?

You own all of the data models we build. Complete documentation, test coverage, and knowledge transfer ensure your team can maintain and extend what we deliver. No specialized AI tools required for ongoing support. No vendor lock-in.

How is this different from hiring in-house data engineers?

We deliver faster results than trying to recruit in a competitive market, with knowledge transfer to internal teams. You get enterprise-level expertise without 6-month hiring cycles or ramping periods.

What if we already have data engineers?

Perfect. Our process augments your team, handling the heavy lifting of implementation while freeing your engineers to focus on product and innovation. We integrate collaboratively with your existing workflows.