Offerings

We build intelligent computer vision and generative AI systems that solve complex imaging problems across life sciences, clinical research, and medical diagnostics.

We accelerate life-changing science by embedding AI into the clinical workflows that matter most — bringing speed, clarity, and confidence to every stage of research. We specialise in modular, human-centered AI systems for mid-market biotech, pharma, and CROs — helping teams move faster without disrupting what already works.

We build intelligent computer vision and generative AI systems that solve complex imaging problems across life sciences, clinical research, and medical diagnostics.

As clinical trial complexity increases and timelines compress, the limitations of manual ADaM dataset programming have become increasingly apparent. The conventional reliance on human-driven R code development introduces variability, slows delivery, and elevates the risk of non-compliance with regulatory expectations.

Research Hub is an AI-powered platform purpose-built for medical writers and regulatory teams seeking precision, speed, and scientific rigour in clinical documentation. By combining literature retrieval, protocol validation, and SAP review into a single system, it streamlines content generation across the documentation lifecycle. The platform interrogates PubMed, ClinicalTrials.gov, and internal sources to extract, summarise, and structure biomedical evidence—tailored to user-defined research questions. It then applies intelligent compliance checks, aligning protocols and analysis plans with regulatory frameworks such as FDA, EMA, ICH, and GCP. Each module—literature synthesis, protocol deviation detection, and SAP alignment—is modular yet interconnected, enabling seamless transitions from drafting to validation. Research Hub eliminates redundant manual review, reduces downstream clarification cycles, and ensures submission-ready, regulator-friendly outputs from the outset.

Cell viability analysis is crucial for understanding cell health, drug responses, and disease mechanisms, yet current lab assessment methods rely on visual inspection, making them time-consuming and laborious effort for skilled lab practitioners.

We accelerate life-changing science by embedding AI into the clinical workflows that matter most — bringing speed, clarity, and confidence to every stage of research. We specialise in modular, human-centered AI systems for mid-market biotech, pharma, and CROs — helping teams move faster without disrupting what already works.

Cell viability analysis is crucial for understanding cell health, drug responses, and disease mechanisms, yet current lab assessment methods rely on visual inspection, making them time-consuming and laborious effort for skilled lab practitioners.

In clinical research, the protocol defines a study's scientific, ethical, and operational foundation. Any misalignment between the protocol and execution can result in regulatory challenges, data inconsistencies, or deviations that compromise study credibility.

As clinical trial complexity increases and timelines compress, the limitations of manual ADaM dataset programming have become increasingly apparent. The conventional reliance on human-driven R code development introduces variability, slows delivery, and elevates the risk of non-compliance with regulatory expectations.

Research Hub is an AI-powered platform purpose-built for medical writers and regulatory teams seeking precision, speed, and scientific rigour in clinical documentation. By combining literature retrieval, protocol validation, and SAP review into a single system, it streamlines content generation across the documentation lifecycle. The platform interrogates PubMed, ClinicalTrials.gov, and internal sources to extract, summarise, and structure biomedical evidence—tailored to user-defined research questions. It then applies intelligent compliance checks, aligning protocols and analysis plans with regulatory frameworks such as FDA, EMA, ICH, and GCP. Each module—literature synthesis, protocol deviation detection, and SAP alignment—is modular yet interconnected, enabling seamless transitions from drafting to validation. Research Hub eliminates redundant manual review, reduces downstream clarification cycles, and ensures submission-ready, regulator-friendly outputs from the outset.

Cell viability analysis is crucial for understanding cell health, drug responses, and disease mechanisms, yet current lab assessment methods rely on visual inspection, making them time-consuming and laborious effort for skilled lab practitioners.