Apoha Emerges From Stealth With $36 Million and Launches VIBE

LONDON and SAN FRANCISCO — June 3, 2026 — Apoha has emerged from stealth with $36 million in cumulative funding and introduced VIBE, its first commercial measurement product. The deep-technology company is building a new class of molecular-behaviour data intended to help artificial-intelligence systems evaluate how medicines, foods and advanced materials perform under real-world stress.

The financing combines a seed round completed in 2024 with a further unlettered round completed in spring 2026. Singular led the latest investment, joined by Draper Associates, while existing investors Redalpine, Seedcamp, Wilbe and Nucleus continued their backing. Apoha has also received grant support from Innovate UK. The company has not disclosed a valuation.

Apoha plans to use the capital to expand its experimental platform, accommodate more sample types and serve more customers. The platform combines purpose-built laboratory hardware, high-dimensional measurements and machine-learning models. Its commercial goal is to give research teams an earlier view of material behaviour, before a weak drug candidate, unstable formulation or unsuitable ingredient absorbs additional time and capital.

A new data layer for molecular behaviour

Conventional analysis can describe molecular sequence, chemical composition or three-dimensional structure. Apoha is focused on another question: how a substance behaves when it is disturbed. A small sample is introduced to an engineered liquid interface and exposed to controlled mechanical, chemical, electrical and thermal stresses. Sensors capture the evolving waves and convert them into a numerical behavioural signature.

The company calls one such measurement a VIBE check. VIBE refers to variations in interfacial behaviour under excitation. According to Apoha, a run can start with only micrograms of material and produce a high-dimensional representation in minutes. The measurement is designed to reveal tendencies including aggregation, gelation, stability, degradation and interaction at an interface.

Rather than treating every signal as an isolated laboratory result, Apoha can compare many behavioural signatures and train models on the relationships among them. Samples that respond similarly may occupy nearby positions in this learned data space even when their sequences or compositions differ. That creates a basis for screening candidates by likely performance, not merely by structural resemblance.

Technical information about the measurement principle is available in Apoha's official science overview.

Initial commercial priorities

• Pharmaceutical research: identify antibody and formulation risks while experimental material is scarce and changes remain affordable.
• Food and beverage development: compare how ingredients and finished formulations behave, including texture and sensory-related characteristics.
• Advanced materials: evaluate stability, wear and other performance attributes before committing to lengthy development cycles.
• Platform expansion: support additional sample classes, increase throughput and build a larger behavioural dataset for model training.

From laboratory signals to earlier business decisions

The immediate value proposition is not to replace every established assay. It is to narrow a field sooner and give scientists another decision layer when failure remains comparatively inexpensive. In drug discovery, that may mean removing an antibody candidate before development advances. In food production, it may mean identifying a replacement ingredient without repeatedly rebuilding and testing a finished product.

Apoha says its work with Boehringer Ingelheim has demonstrated the ability to identify high-risk antibody candidates with greater than 90% precision using very small quantities of material. The company has also applied its approach to food formulations and is working with organizations in biotechnology and materials. These projects provide early commercial data while the wider platform continues to develop.

The company reports approximately 40 customer projects completed and a team of about 25 people at the time of launch. Its operations span London and San Francisco. Co-founder and chief executive Shamit Shrivastava developed the underlying liquid-wave analysis methods and related instrumentation; co-founder and chief operating officer Anshika Srivastava is leading the effort to scale the platform and the business.

Readers can review the founders and wider organization on Apoha's official company page.

What the $36 million milestone changes

Emerging from stealth moves Apoha from private technology development into a more visible commercial phase. The financing gives the company room to standardize its hardware, broaden experimental coverage and collect more measurements. Each of those steps matters because the usefulness of a behavioural model depends on both the quality of individual experiments and the scale and diversity of the resulting dataset.

The milestone also places practical limits around the announcement. The $36 million is cumulative funding rather than a newly announced Series A round, and the company has not provided a valuation. Commercial adoption will depend on reproducible performance across materials, integration into customer workflows and evidence that earlier predictions improve development economics.

Apoha's next phase will therefore be measured by more than funding. Relevant indicators include the number of sample types supported, throughput, validated customer outcomes and the ability to translate complex wave data into clear go-or-no-go decisions for research teams. The company enters that phase with a commercial product, initial partnerships and capital intended to expand both hardware and models.

About Apoha

Apoha Limited is a deep-technology company developing Liquid State Intelligence, a platform that measures molecular behaviour at engineered liquid interfaces and turns the resulting signals into data for artificial-intelligence models. Founded in 2021, the company operates in London and San Francisco and works across pharmaceutical, food, biotechnology and materials applications.