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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Converge Bio announced a $25 million oversubscribed Series A on January 13, 2026, led by Bessemer Venture Partners. TLV Partners, Vintage Investment Partners, Saras Capital, and executives associated with Meta, OpenAI, and Wiz also participated. The company says the financing brings its disclosed funding to about $30 million, including a $5.5 million seed round announced in 2024.
Converge is building enterprise AI systems for biotech and pharmaceutical research—not a consumer chatbot and not an approved-drug company. Its software is designed to help researchers choose which biological candidates to create and test in the laboratory.
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What Converge Bio does
Converge Bio is a Boston- and Tel Aviv-based generative-AI biotech company founded by Dov Gertz, Oded Kalev, and Dr. Iddo Weiner. It trains models on biological information such as DNA, RNA, and protein sequences, then combines those models into research workflows for pharmaceutical and biotechnology companies.
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Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →The company describes its approach as an “AI-Lab partner.” In practice, that means generating or analyzing biological designs, predicting their properties, ranking candidates, and supporting the experiments needed to validate them. The platform does not eliminate synthesis, assays, toxicology, clinical trials, or regulatory review.
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Its current product suite includes ConvergeAB for antibody design and screening, ConvergeGEO for protein-expression optimization, and ConvergeCELL for virtual-cell simulation and related target or biomarker work.
How the $25 million round breaks down
- Round: $25 million Series A
- Lead investor: Bessemer Venture Partners
- Institutional participants: TLV Partners, Vintage Investment Partners, and Saras Capital
- Additional backers: Executives associated with Meta, OpenAI, and Wiz
- Previously announced financing: $5.5 million seed round led by TLV Partners in November 2024
- Total disclosed funding: about $30 million, according to the company
The “about” qualification matters. Adding the disclosed $25 million Series A to the $5.5 million seed round produces $30.5 million, while company materials describe the total as $30 million. The safest description is therefore “about $30 million” or “$30 million, according to the company.”
Converge’s funding announcement is dated January 13, 2026. One line in the company’s announcement body reportedly says January 13, 2025, which appears to be a typographical error; independent coverage also dates the announcement to January 13, 2026.
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What customers can use the platform for
Antibody design
ConvergeAB is intended to support several stages of antibody research, including de novo candidate generation, affinity maturation, humanization, developability assessment, and candidate ranking.
The company describes a workflow that can generate antibody sequences, predict characteristics such as binding, stability, solubility, immunogenicity, and developability, and use structural or docking-based analysis to estimate how candidates may interact with a target. Selected sequences can then be synthesized and tested in the laboratory.
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That is different from asking a general-purpose language model to invent a protein sequence. TechCrunch reported that Converge uses a combination of generative models, predictive models, physics-based systems, traditional machine learning, statistical methods, and language models for supporting tasks such as literature navigation. The company’s CEO said text-based LLMs are not its core biological model.
Protein-expression optimization
ConvergeGEO focuses on improving how proteins are produced. The company says its system can help optimize coding sequences, untranslated regions, promoters, and terminators for particular host organisms and expression systems.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsConverge reports that a case study involving PreFer Industries produced a 4.5-times increase in protein yield. That is a company-published result, not an independently audited benchmark. The important unanswered questions for buyers include the baseline conditions, number of constructs tested, controls, replication, and whether the improvement persists during commercial-scale production.
Targets and biomarkers
The platform is also intended to analyze biological data to identify disease-driving targets, patient-response relationships, and cell-type-specific signals. The company’s current website lists ConvergeCELL as a virtual-cell solution, although the January funding announcement emphasized target discovery, antibody design, and protein-manufacturing optimization.
What evidence does Converge have beyond the pitch?
Converge says more than a dozen pharmaceutical and biotech customers were using its solutions and that it had completed more than 40 programs. TechCrunch reported that customers spanned the United States, Canada, Europe, and Israel, with expansion into Asia discussed by the company.
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The company has also reported:
- Single-digit-nanomolar antibody-binding results in one program.
- Protein-yield improvements of roughly four to seven times in customer work.
- Biomarker discoveries.
- A 4.5-times protein-yield increase in the PreFer case study.
These figures indicate commercial and experimental activity, but they do not establish clinical success. The public funding announcement does not identify an approved medicine, a clinical-trial result, or an independently audited customer-performance dataset. A reported binding result is not clinical efficacy, and a higher protein yield is not automatically a lower-cost or scalable manufacturing process.
Why Bessemer and technology executives might invest
The investment fits a broader venture-capital interest in applying AI to expensive, data-intensive scientific workflows. Pharmaceutical research represents a large enterprise market, and software that reduces the number of candidates sent to the laboratory could create value even if it does not replace laboratory work.
Converge is also positioning itself as more than a provider of raw model access. Its pitch combines multiple model types, workflow-specific tools, deployment options, and scientific support. That may be attractive to pharmaceutical teams that need an integrated process rather than a standalone model.
The early customer and program counts provide additional commercial evidence. Bessemer’s role as lead investor and reported board participation also give the round institutional credibility.
The technology-executive participation should be interpreted more narrowly. Public coverage identifies executives associated with Meta, OpenAI, and Wiz as participants, but does not provide a complete list or detailed investment amounts. Their involvement does not mean those companies invested, endorsed a therapeutic program, or guaranteed Converge’s commercial or scientific success.
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- 【Optimal Focal Length Range】3-60 mm. To ensure image sharpness, please ensure that the distance between the microscope lens and the object being observed is maintained within the range of 3-60 mm.
What the new funding will be used for
Available coverage says Converge plans to use the capital to expand its platform, grow its team, deepen partnerships with pharmaceutical and biotechnology companies, and continue development across the drug-development lifecycle.
The company has not publicly disclosed a valuation, dilution figure, revenue target, detailed hiring plan, or investor-by-investor allocation. TechCrunch reported that the team had grown to 34 employees from nine in November 2024, but headcount can change quickly and should not be treated as a current figure without a newer disclosure.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.The key risks and unanswered questions
For investors, partners, and prospective customers, the funding is a signal of confidence—not proof that the technology works across every biological problem. The most important questions are practical:
- Experimental validation: What percentage of generated candidates succeed in customer assays, and how does that compare with existing internal methods?
- Generalization: Does performance transfer across targets, organisms, disease areas, assay conditions, and expression hosts?
- Calibration: Do confidence scores reliably distinguish strong candidates from plausible but unusable ones?
- Multi-objective optimization: Does improving affinity harm stability, solubility, immunogenicity, manufacturability, or another property?
- Data governance: Are customer sequences used to train shared models, and who owns generated sequences and outputs?
- Integration: Can results move into existing laboratory-information, sequence-design, and contract-research workflows?
- Economics: Does the software reduce total research costs, or does it simply shift spending from computational screening to additional laboratory validation?
Converge says private deployments isolate customer data and that customers retain ownership of sequences and outputs. Those are product and contractual claims that buyers should verify in agreements, security documentation, and data-processing terms.
Who is the platform for?
Converge’s offering appears aimed at pharmaceutical companies, biotech businesses, biomanufacturers, and research organizations with scientific staff, proprietary data, and laboratory capacity. Its website emphasizes “Request Access,” managed infrastructure, and customer-cloud deployment rather than public self-service pricing.
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That makes the platform a poor fit for individual researchers, students, or hobbyists who cannot conduct follow-up experiments. The value of AI-assisted biological design depends on the complete loop: prediction, synthesis, testing, learning, and repeat optimization.
Potential buyers should clarify whether the system is hosted by Converge or deployed in the buyer’s cloud; what APIs and export options are available; whether proprietary data can be used for private fine-tuning; what happens to data after termination; and whether pricing is based on users, compute, programs, milestones, or enterprise contracts. No standard public subscription or enterprise price is disclosed in the reviewed materials.
Bottom line for business and finance readers
Converge Bio’s Series A is substantial early-stage financing for a company that says it already has more than a dozen biotech and pharmaceutical customers and more than 40 completed programs. Bessemer’s lead role is the central institutional signal; the participation of executives associated with Meta, OpenAI, and Wiz adds visibility but should not be mistaken for scientific validation.
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