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.

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.

Outcomes

Real Clients, Real Results

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-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

UBB Metrics and ARR Forecasting at Scale

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

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

Testimonials

Proven at Scale, Delivered with Impact

"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
"Working with the Mammoth Growth team has saved me a ton of time generating reports and datasets. Within 6 weeks I had fully modeled data AND an interface to extract it, so I don't have to write a query every time my team comes to me with questions."
Dana McLeod
VP, Financial Planning & Analysis - LegalShield
How It Was Built

How We Built AI
That Actually Delivers

Our ai-data-agent was engineered with:

A decade

of hands-on data consulting

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

Our ai-data-agent was engineered with:

60x

Faster Deliverable Speed

Our proprietary agents accelerate delivery, dramatically reducing the time it takes to generate a production-ready data deliverable.

20-hour coding projects in 20 minutes, 10-hour requirements in 10 minutes

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.

FAQ

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 Analyst AI 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. This requires commitment: attend scheduled calls, clearly articulate your needs, and approve work promptly to keep us unblocked. The heavy technical work happens on our end, but project momentum depends on your timely input and decisions.

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.

Next Step

Schedule your next working
session with our team

No pressure. Just a straightforward conversation about how we can help you move faster.