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Enveda Tech Stack

AI-powered natural product discovery platform for drug development

Biotechnology Research Boulder, CO 201–500 employees Founded 2019 Privately Held

Enveda combines wet-lab automation (NMR, LC-MS, HPLC) with ML infrastructure (PyTorch, Databricks, Azure) to mine unexplored molecules from living organisms for drug discovery. The hiring mix—research-heavy with emerging AI and data roles, plus a VP-level AI Innovation Director—reveals a company scaling from molecular characterization toward ML-driven lead optimization. Pain points cluster around workflow automation and data quality (mis-annotations, inventory), not raw compute.

Tech Stack 13 technologies

Core StackSAP Python Pandas NumPy PyTorch Vue Databricks Lever LC-MS Azure HPLC UPLC-MS UPLC

What Enveda Is Building

◆Challenges

Accelerating drug discovery
Uninterrupted experimental workflows
Inventory accuracy
Mis-annotations in metabolite data
Speeding up drug discovery
Delivering leads to clinical pipeline
Cost effectiveness
Integrating ai across translational sciences
Mental health drug discovery
Streamline drug discovery workflows

▲Active Projects

Advanced nmr experiments for natural product structure elucidation
Automation of nmr experiments using iconnmr
Machine learning for mass spectrometry
Computational biology and chemistry projects
Lead generation and lead optimization of pipeline projects
Ai integration across development and translational sciences
Ai-driven strategies for preclinical and clinical research
Scalable ai tools for translational research
Discovery of natural product-derived bioactive compounds
Validation of biological evaluation

Hiring Activity

Steady15 roles · 4 in 30d

Department

Research

8

Data

2

Design

1

Engineering

1

HR

1

Manufacturing

1

Ops

1

Seniority

Mid

6

Director

3

Manager

2

Senior

2

Intern

1

VP

1

Notable leadership hires: AI Innovation Director, CMC Director

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About Enveda

Enveda is a biotech company founded in 2019 that discovers drug candidates by analyzing chemical structures produced by natural organisms, building what it describes as a database of chemical biodiversity. The platform applies AI and computational chemistry to identify promising molecules and advance them toward clinical trials. The company operates across three layers: laboratory automation (NMR and mass spectrometry), computational modeling (machine learning on spectral and structural data), and translational research (lead optimization and preclinical evaluation). Based in Boulder, CO with 201–500 employees, Enveda sells into pharma R&D organizations seeking faster, lower-cost pathways to drug discovery.

HeadquartersBoulder, CO

Company Size201–500 employees

Founded2019

Hiring MarketsIndia, United States

Frequently Asked Questions

What tech stack does Enveda use?

Enveda's core stack spans lab automation (LC-MS, HPLC, UPLC-MS, NMR via iConnNMR), data processing (Python, Pandas, NumPy), ML (PyTorch), analytics (Databricks, Azure), and SAP for ERP. Vue handles front-end interfaces.

What is Enveda working on?

Active projects focus on NMR automation for natural product structure elucidation, machine learning for mass spectrometry, lead generation and optimization, AI-driven preclinical research strategies, and integrating AI across translational sciences pipelines.