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Antibody Design and Engineering

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ConvergeAB™ is our antibody design and optimization SaaS-based solution. We support candidate selection, lead optimization and de novo generation across formats like IgG, VHH, scFv and bispecifics. Powered by generative and predictive models, it explores a broad sequence space and ranks candidates by binding, developability and structural fit.

ConvergeAB™ is our antibody design and optimization SaaS-based solution. We support candidate selection, lead optimization and de novo generation across formats like IgG, VHH, scFv and bispecifics. Powered by generative and predictive models, it explores a broad sequence space and ranks candidates by binding, developability and structural fit.

Speed

Accelerate antibody discovery with Gen AI-powered design and ranking of candidates, significantly shortening timelines by replacing slow, iterative lab work with rapid, guided predictions.

Speed

Accelerate antibody discovery with Gen AI-powered design and ranking of candidates, significantly shortening timelines by replacing slow, iterative lab work with rapid, guided predictions.

Cost

Eliminate costly trial-and-error by rapidly identifying optimal antibody candidates early. Avoid expensive screening cycles and reduce dependence on animal experiments to significantly lower discovery costs.

Cost

Eliminate costly trial-and-error by rapidly identifying optimal antibody candidates early. Avoid expensive screening cycles and reduce dependence on animal experiments to significantly lower discovery costs.

Precision

Engineer antibodies for specificity and developability by integrating epitope, manufacturability and immunogenicity constraints from the start. Reduce risk with optimization of structural and functional fit.

Precision

Engineer antibodies for specificity and developability by integrating epitope, manufacturability and immunogenicity constraints from the start. Reduce risk with optimization of structural and functional fit.

Generate

Predict

Explain

Predict binding & developability

Generate

Predict

Explain

Predict binding

01

01

Generate diverse antibody candidates in silico

Optimized antibody candidates, generated with unprecedented speed and precision. Define your target and optional design constraints, and ConvergeAB rapidly generates diverse sequences with strong binding affinity, structural stability, and functional relevance.

Optimized antibody candidates, generated with unprecedented speed and precision. Define your target and optional design constraints, and ConvergeAB rapidly generates diverse sequences with strong binding affinity, structural stability, and functional relevance.

Start generating

02

02

Better leads,
fewer cycles

Optimize affinity, stability, solubility, immunogenicity and expression in a single pass. Each lead reflects millions of in silico designs, ranked and filtered to maximize your chances of success with fewer rounds in the lab.

Optimize affinity, stability, solubility, immunogenicity and expression in a single pass. Each lead reflects millions of in silico designs, ranked and filtered to maximize your chances of success with fewer rounds in the lab.

Start optimizing

03

03

Prioritize high-performing candidates before entering the lab

ConvergeAB screens millions of antibody sequences per target, evaluating each for affinity, developability, epitope specificity, humanization and structural fit. Detailed scores and visual outputs support confident selection, accelerating discovery while reducing experimental burden.

ConvergeAB screens millions of antibody sequences per target, evaluating each for affinity, developability, epitope specificity, humanization and structural fit. Detailed scores and visual outputs support confident selection, accelerating discovery while reducing experimental burden.

Start screening

04

04

Generate, optimize and screen - all in one single platform

Each candidate comes with detailed predictive profiles including affinity, stability, solubility, immunogenicity and docking-based structural fit. Review key metrics, explore 3D visualizations and export the most promising sequences for synthesis. Whether you’re testing in-house or working with a CRO, you move ahead with confidence and clarity.

Each candidate comes with detailed predictive profiles including affinity, stability, solubility, immunogenicity and docking-based structural fit. Review key metrics, explore 3D visualizations and export the most promising sequences for synthesis. Whether you’re testing in-house or working with a CRO, you move ahead with confidence and clarity.

Start designing

"With ConvergeAB, your data and sequences remain fully private and under your control. Each deployment is provisioned as a dedicated, isolated instance, ensuring that your data is never shared, exposed or used outside your organization. All outputs are exclusively yours, with full ownership and IP retained at every stage."

Dov Gertz

|

CEO & Co-Founder

Private by design

Only your team can access your data. We don’t share, reuse, or train on it. Your privacy is always protected.

Complete ownership

All sequences and outputs belong to you, with no royalties or restrictions. You have full rights and control.

Fully managed

We handle infrastructure end-to-end, from setup to scaling, so your team can focus entirely on the science.

Expert support

Our scientists and AI experts guide you through every stage, ensuring smooth design and discovery.

How it works

How it works

ConvergeAB™ is trained on over 1 trillion natural protein tokens, including 7 million antibody sequences, 3 million antibody–antigen pairs, and 10,000 developability measurements. This foundation enables affinity maturation, developability optimization, humanization, patent escape and IP expansion, and candidate screening across IgG, ScFv, and VHH (Beta) formats.

Input

Explainability & Output

A Classification Head links the patient representation to clinical outcomes. The model then extracts Disease-specific association scores and Cell-type-gene importance scores. This explainability allows us to extract the genes that are the main drivers for a specific disease or response.

Explainability & Output

A Classification Head links the patient representation to clinical outcomes. The model then extracts Disease-specific association scores and Cell-type-gene importance scores. This explainability allows us to extract the genes that are the main drivers for a specific disease or response.

2nd

Predictors

Explainability & Output

A Classification Head links the patient representation to clinical outcomes. The model then extracts Disease-specific association scores and Cell-type-gene importance scores. This explainability allows us to extract the genes that are the main drivers for a specific disease or response.

Explainability & Output

A Classification Head links the patient representation to clinical outcomes. The model then extracts Disease-specific association scores and Cell-type-gene importance scores. This explainability allows us to extract the genes that are the main drivers for a specific disease or response.

2nd

Output

Explainability & Output

A Classification Head links the patient representation to clinical outcomes. The model then extracts Disease-specific association scores and Cell-type-gene importance scores. This explainability allows us to extract the genes that are the main drivers for a specific disease or response.

Recent Updates

Resources Page

Case Study

Generating Clinic-Ready Antibodies: Benchmarking ConvergeAB™ Against Blockbuster Drugs

February 16, 2026

Case Study

3D ribbon-like protein structure with yellow segments marking editable regions and grey segments marking non-editable regions. Text on the left reads ‘Intellectual Property Expansion’ with a small color legend for editable and non-editable areas

AI-driven IP expansion: scientific and operational breakthroughs using innovative antibody design

December 3, 2025

Blog

Solubility: The Quiet Deal-Breaker in Antibody Development

January 6, 2026

Recent Updates

Case Study

Generating Clinic-Ready Antibodies: Benchmarking ConvergeAB™ Against Blockbuster Drugs

February 16, 2026

Case Study

3D ribbon-like protein structure with yellow segments marking editable regions and grey segments marking non-editable regions. Text on the left reads ‘Intellectual Property Expansion’ with a small color legend for editable and non-editable areas

AI-driven IP expansion: scientific and operational breakthroughs using innovative antibody design

December 3, 2025

Blog

Solubility: The Quiet Deal-Breaker in Antibody Development

January 6, 2026

Resources Page

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Start designing
better antibodies

Access ConvergeAB

pixelized colorful circle

Start designing
better antibodies

Access ConvergeAB