Experience

A team combining academic rigor with production-grade data systems. Methodologies built for transparency and reproducibility.

Our Background

Gravitas Grove brings together specialists in quantitative analysis, machine learning, and government data systems. Our team has built automated pipelines serving over 1,000 clients, developed predictive models across agricultural, financial, and economic domains, and managed production systems operating continuously for years. We've conducted large-scale research spanning millions of forecasts across diverse methodologies—ARIMA, VAR, LASSO, Random Forest, XGBoost, and neural networks. This foundation in rigorous, reproducible research translates directly to the documentation and methodology standards government agencies require.

Representative Capabilities

Selected projects demonstrating our team's analytical capabilities and technical approach.

Agricultural Export Prediction System

National Agricultural Intelligence Firm

Scope

ML pipeline for grain export forecasting integrating USDA, Census, and trade data

Approach

Docker-containerized machine learning models, automated data ingestion, ensemble methods

Results

Soybean export predictions achieving R² of 0.79-0.81; corn R² of 0.40-0.43

Technologies

Python, scikit-learn, Docker, PostgreSQL, USDA FAS, Census Trade APIs

Large-Scale Predictive Modeling Research

Academic Research Partnership

Scope

Comprehensive evaluation of predictability across 50 commodity and financial markets

Approach

13 forecasting methodologies—ARIMA, VAR, LASSO, Random Forest, XGBoost, neural networks

Results

3.7M+ out-of-sample forecasts; peer-reviewed findings on predictability limits

Technologies

Python, R, scikit-learn, TensorFlow, high-performance computing cluster

Market Intelligence Platform

Agricultural Analytics Provider

Scope

End-to-end data systems for agricultural market analysis

Approach

Automated pipelines from USDA, exchange data, proprietary sources; daily reporting

Results

1,000+ end users served; system operated continuously for 6+ years

Technologies

Python, SQL, automated ETL, reporting automation

Our Methodology

Every engagement follows a structured approach designed for reproducibility and transparency.

1

Data Assessment

Evaluate available data sources, identify gaps, establish quality metrics

2

Pipeline Development

Build automated ingestion, cleaning, and transformation systems

3

Analysis & Modeling

Apply appropriate statistical methods with documented assumptions

4

Validation

Test results, sensitivity analysis, peer review of methodology

5

Delivery & Documentation

Transfer deliverables with full SOPs and training

How We Work

We offer flexible engagement models to match your agency's needs and procurement requirements.

2-4 weeks

Pilot Project

2-4 week focused engagement to evaluate fit. Fixed scope, fixed price, full deliverables. Ideal for agencies new to working with us.

Most Common
4-16 weeks

Project-Based

Defined scope with clear deliverables and timeline. Title VI analyses, housing assessments, custom dashboards. Most common engagement type.

Monthly

Ongoing Support

Monthly retainer for agencies needing continuous analytics support, data pipeline maintenance, or recurring reporting.

Pilot Project Program

For agencies evaluating new analytics partners, we offer structured pilot engagements. Start with a focused project—a single Title VI analysis, a housing data assessment, or a custom dashboard—to evaluate our work before committing to larger scopes.

Discuss a Pilot Project

References: Client references and detailed project documentation available upon request for qualified procurement officers.