Your Long-Term AI Partner for Biotech Innovation
Custom ML systems, scientific-grade infrastructure, and AI-powered workflows for biotech teams at every stage
Where we support biotech teams
across the entire R&D lifecycle
Seed / Pre-Seed
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Scientific AI proof-of-concept (PoC)
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Rapid prototype/MVP for investor validation
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Target discovery mini-engine
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Lightweight scalable pipelines (ready for post-funding growth)
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Biomarker/feature-space exploration
Series A
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End-to-end R&D workflow automation
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Multi-omics pipelines (scRNA-seq, bulk RNA, proteomics, metabolomics)
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Custom ML models trained on internal datasets
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Standardized, reproducible data processing environments
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Scientific data infrastructure setup
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Integration of AI tools into wet-lab & dry-lab workflows
Series B & Scaling
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Migration to scalable scientific AI platforms
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Unified architecture for multiple therapeutic programs
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Enterprise-grade compliance (HIPAA/GDPR/PHI)
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Full workflow orchestration + CI/CD for AI
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Integration with LIMS/ELN and internal R&D systems
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Cross-team knowledge-graph–based retrieval
Therapeutics & Drug Discovery
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Molecular space exploration with embeddings & generative AI
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Candidate scoring & ranking
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Toxicity/off-target prediction
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Lead optimization engines (ADMET, docking prioritization)
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Custom protein/structure ML models
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Protein–protein interaction (PPI) modeling
We build AI-first biotech products end-to-end – with scientific correctness, scalable engineering, and enterprise compliance
Learn more about our Biotech ExpertiseData Infrastructure for Biotech Products
We build: pipelines, harmonization layers, datastores optimized for scientific data types, permissioning, regulatory-ready logging.
Product Vision, Architecture & Roadmapping
We translate scientific ideas into actionable product strategies: feature discovery → technical architecture → risk analysis → delivery sequencing.
R&D Workflow Automation & Platform Logic
We engineer the backbone of biotech platforms: experiment workflows, QC/QA steps, LIMS/ELN integration, data validation layers, auditability, lineage tracking.
Scientific AI Engines & ML System Design
Architecture and development of the core ML modules behind your product: structure prediction engines, multi-omics models, graph-based retrieval, LLM agents, generative models.
Full-Stack Product Development & UI/UX for Scientists
Front-end, back-end, APIs, dashboards, experiment builders, visualizations.
Enterprise Deployment & Scaling
Cloud orchestration, CI/CD for scientific ML, MLOps, reliability engineering, monitoring, validation workflows, security, compliance.
Didn’t find exactly what you were looking for?
Tell us what you’re building – we’ll map out the options, evaluate feasibility, and recommend the optimal technical pathway.
Get a consultationBiotech
Industry
USA
Location
AI Ops & MLOps, Cloud Architecture, UI/UX Design
Services
$200,000 to $999,999
Budget
The team surpassed expectations on timelines, provided much needed guidance and overall input on design, all while operating with a high degree of autonomy.
Carl Kaub
Vice President of Chemistry at HTG Molecular DiagnosticBusiness Impact You Can Expect
Book Strategy Call2–4×
faster product delivery from concept → productionClear architecture, structured workflows, and aligned teams reduce engineering delays.
60%
lower R&D platform development costsWe eliminate duplicated engineering, legacy rebuilds, and data rework.
2×
Higher Early-Phase Success RatesImproved toxicity, efficacy, and PPI prediction leads to dramatically fewer failures in early clinical phases.
Enterprise-grade
reliability from day oneCI/CD for scientific ML, versioning, traceability, and compliance built-in.
Scalable
multi-omics & scientific data foundationYour product grows with pipelines, cohorts, and programs – not against them.
Let’s build your AI advantage
Whether you’re prototyping a molecule scoring system or looking to automate your clinical ops – we’ll help you turn your biotech data into competitive edge.
Book a Meeting
