Accelerate discovery with an execution platform engineered for scientific rigor. QURE Science unifies computer-vision guided execution, domain-native AI, telepresence collaboration, and governed data pipelines—so every experiment is reproducible, traceable, and fast.
Step-aware guidance keeps scientists aligned to the validated method across shifts, sites, and partners.
Time-stamped actions, media, deviations, and attestations are recorded as the work happens.
Validated execution traces become the substrate for AI scientist planning and closed-loop optimization.
Ensure every scientist performs protocols the same way—every time. AI-anchored computer vision guidance removes operator-dependent variability, enforces correct technique in real time, and validates each step as it happens. Standardization scales across shifts, geographies, CRO partners, and program phases.
QURE Science detects deviations, timing drift, incorrect tool use, ergonomic risks, and environmental mismatches—then corrects them instantly. This reduces failed runs, rework cycles, reagent waste, and batch inconsistencies.
Every step is captured with time-stamped logs, versioned protocols, and full chain-of-custody metadata. Generates QA- and GxP-aligned evidence packages suitable for submissions and audits.
Agent copilots analyze historical runs, literature, telemetry, and simulation outputs to identify failure points, propose next-step experiments, and accelerate hypothesis → execution → insight cycles.
Scientists, automation engineers, and computational teams can “beam in” remotely to observe live execution through the operator’s live view. They can annotate, guide, verify critical steps, and collaborate across sites—reducing tech-transfer friction, accelerating troubleshooting, and enabling distributed experimentation.
QURE Science harmonizes wet-lab instruments, robotics, ELNs, LIMS systems, and computational models—forming a governed, lineage-tracked institutional knowledge graph.
QURE Science provides the structured, validated execution data that autonomous discovery systems depend on.
Its real-world semantics enable:
QURE Science is an ambient intelligence platform for pharmaceutical and biotech labs. It uses computer vision and AI to guide protocol execution, automatically capture GxP-compliant data, assist with experiment planning, and enable telepresence collaboration — making every experiment reproducible, traceable, and faster.
Computer vision monitors protocol timing, positioning, and technique in real time so different operators across sites execute the exact same steps and validations. This eliminates operator-dependent variability, producing reproducible results across shifts, geographies, CRO partners, and program phases.
Every action is time-stamped with role-based attestations, SOP versions, and environmental metadata. QURE Science generates QA- and GxP-aligned evidence packages with full chain-of-custody suitable for regulatory submissions and audits, with 100% automated reporting.
QURE Science integrates with Electronic Lab Notebooks (ELNs), Laboratory Information Management Systems (LIMS), robotics controllers, simulation engines, and Manufacturing Execution Systems (MES) for closed-loop orchestration and lineage-tracked data pipelines.
AI copilots within QURE Science analyze historical runs, scientific literature, instrument telemetry, and simulation outputs to identify failure points, propose next-step experiments, and accelerate the hypothesis-to-execution-to-insight cycle.
Yes. Adaptive caching and edge inference let operators continue AI-guided work during connectivity drops, syncing securely when links are restored. QURE Science also supports full on-premises and air-gapped deployment for regulated environments.
Data routes through encrypted channels with strict access policies. Sensitive frames can be redacted on-device before storage or sharing. QURE Science supports secure cloud, on-premises, and air-gapped deployments to meet the data sovereignty requirements of regulated industries.
AI-generated protocol guidance is versioned, tested against golden runs, and gated by human review before deployment to production. Validated execution traces and deviations feed back into the model with governance controls, opt-in scopes, and full auditability.
Our experts are ready to collaborate on pilots, integrations, and scaled deployments.