Senior-level expertise, applied directly to your problem
Many organizations encounter scientific and analytical challenges that don't warrant hiring a full-time specialist — but require genuine expertise to solve correctly. We provide on-demand access to PhD and MSc-level scientists with backgrounds in computational biology, machine learning, and data science.
When you need more than a generalist IT firm can offer
Consulting from a generalist IT firm can address process and tooling questions, but it rarely addresses the underlying scientific or analytical challenge. When a research institution needs help interpreting sequencing results, or a business needs someone who understands statistical validity — general IT consulting isn't enough.
AGRV Solutions bridges computer science and the biological and data sciences. Our founders have hands-on research experience in molecular biology, ecological modeling, machine learning, and data infrastructure — applied directly to every client engagement.
Academic-Grade Rigor
Our founders come from research environments where statistical validity and methodological soundness are non-negotiable — we bring that standard to every engagement.
Domain-Specific, Not Generic
We work in health sciences, computational biology, agriculture, ecology, and data science — not "all industries." That depth means we understand your problem faster.
Hourly or Fixed-Scope
A single afternoon of expert review, a week of embedded analysis, or a multi-month research partnership — we scope to what you actually need.
Expertise that crosses disciplines
Senior-Level Expertise
Every consulting engagement is handled directly by our founders — a PhD scientist and an MSc data scientist. No work is delegated to junior staff or subcontractors. You get the most experienced people on your problem, every time.
Science Meets Engineering
We sit at the intersection of biological science and software engineering — a rare combination that allows us to bridge the gap between domain knowledge and technical implementation. We can both understand the science and build the tools to advance it.
Measurable Outcomes
We focus on results that can be acted on — reports you can publish, decisions you can defend, workflows you can repeat. Every engagement produces documented, reproducible work with clear methodology that you own and can audit.
Four consulting disciplines
Operations & Workflow Optimization
Assessment and redesign of data workflows and operational processes to eliminate bottlenecks, reduce error rates, and improve throughput. We analyze your current processes, identify inefficiencies, and recommend — or build — improvements with measurable impact on output and staff time.
Statistical Modeling & Interpretation
Design and application of statistical models appropriate to your data and research questions, including selection of the right test or approach, validation of assumptions, interpretation of results, and preparation of findings for internal reports, grant applications, or peer-reviewed publication.
Health Sciences & Biological Data
Specialized consulting in molecular biology workflows, next-generation sequencing (NGS) design and analysis, HIPAA-compliant health data modeling, and the statistical interpretation of clinical or laboratory data. We bring research-grade scientific rigor to health data challenges.
Environmental & Agricultural Analytics
Application of quantitative methods to environmental monitoring datasets, agricultural field data, wildlife survey records, and water management data. We help translate raw field observations into defensible, actionable metrics suitable for regulatory reporting, grant applications, or conservation decision-making.
Domain knowledge backed by technical capability
We apply specialized scientific and analytical tools appropriate to each domain. Below is a representative overview of the methodologies and platforms we work with across our consulting disciplines.
| Domain | Methods & Tools |
|---|---|
| Statistical Analysis | Parametric & non-parametric tests, regression, ANOVA, power analysis, Bayesian methods (Python / R / MATLAB) |
| Machine Learning & Modeling | scikit-learn, XGBoost, PyTorch, custom model development, cross-validation, feature selection |
| Molecular Biology & Genomics | NGS pipeline design, BioPython, sequence alignment, variant calling, differential expression analysis |
| Health Sciences Data | HIPAA-compliant data handling, survival analysis, clinical trial data structures, EHR data interpretation |
| Environmental & Agricultural | Spatial data analysis, time-series modeling, biodiversity indices, remote sensing data, GIS integration |
| Reporting & Visualization | R Markdown, Jupyter Notebooks, Plotly / Dash, ggplot2, publication-ready figure generation |
Common scenarios we solve
NGS experimental design and analysis pipeline
A molecular biology lab is designing a next-generation sequencing study but lacks in-house bioinformatics expertise. We design the experimental protocol, build the analysis pipeline, and interpret the results in the context of the research question.
HIPAA-compliant patient data modeling
A regional clinic wants to analyze longitudinal patient data to identify outcome predictors — but needs a statistical approach that is both scientifically valid and compliant with HIPAA data handling requirements for analysis performed on-premises.
Wildlife survey data analysis and reporting
A state wildlife agency has accumulated years of survey data across multiple species and habitats. We design a quantitative analysis framework that produces defensible population trend estimates and generates outputs suitable for regulatory filings.