
SciSure helps scientific organizations replace fragmented, disconnected systems with a single governed platform for managing lab operations, so teams spend less time reconciling data across tools and more time on research. By combining Electronic Lab Notebook (ELN), Laboratory Information Management System (LIMS), and Health & Safety (EHS) capabilities in one system, SciSure improves reproducibility, strengthens visibility into day-to-day lab activity, and helps organizations reduce risk as they scale. Researchers document experiments, protocols, and results in a structured, searchable digital format with customizable templates and version control, replacing paper notebooks and scattered files. Samples are tracked from intake through processing, storage, and disposal, maintaining full lineage and chain-of-custody records alongside chemical and general lab inventory management and workflow automation. Health & Safety functionality is built into the same platform, covering chemical inventory alongside Safety Data Sheets (SDS), regulatory compliance workflows, and audit readiness, so labs don't need a separate system to stay compliant and audit-ready.
Labs can also extend the platform through an optional marketplace of add-ons, so they can bring in additional capability, like AI-powered support, automated data analysis, protocol generation, toxicity prediction, and image analysis, only where it adds value, without disrupting the rest of their workflow or committing to features they don't need. SciSure also connects directly to lab instruments, external databases, and third-party tools, so data moves between systems without manual re-entry.
SciSure supports both cloud and dedicated hosting, giving organizations control over the deployment model that fits their infrastructure, security, and compliance requirements. It's built to serve academic institutions, biopharma and biotech companies, and start-ups alike, with role-based support for scientists, lab operations staff, safety and compliance teams, leadership, and IT professionals, so the platform works the way each type of user actually needs it to.
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Digital advertisers lose billions every year to invalid traffic, and most do not know it is happening. Fake clicks, bots and click farms are only part of it. The bigger drain is non-incremental traffic: excessive clickers with no intent to convert, and navigational traffic that would have found your brand anyway. All of it inflates cost and corrupts the data your optimisation depends on.
TrafficGuard sits inside the advertising journey and verifies traffic in real time, before it reaches your campaigns. Our approach is surgical, not blunt force. Statistical invalidation removes the invalid and protects the genuine, with full transparency into exactly what was actioned and why. The result is cleaner signals, more accurate reporting, and ad spend that reaches real, high-intent users.
One platform protects every channel that matters:
- Search (Google Search & Performance Max)
- Meta (Instagram & Facebook)
- Affiliate
- Mobile
Start with a free 30-day audit in detection mode and see exactly how much invalid traffic is hitting your campaigns. Switch on prevention when you are ready. Backed by expert onboarding and responsive support, TrafficGuard is built to scale with your spend.
Trusted by 10,000+ advertisers across multiple industries
TrafficGuard is part of Adveritas, publicly listed and accountable on the Australian Securities Exchange (ASX:AV1).
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Shieldstral
Shieldstral is a 3B open-weights, policy-adaptive multimodal safety classifier designed to evaluate text, images, and text-plus-image content using policies defined at inference time. Instead of relying on a fixed taxonomy of harm categories, it frames moderation as a binary question-answering task: users provide an instruction describing the evaluation context and strictness, a yes-or-no safety question, and the content to judge. The model reads the “yes” and “no” logits and converts them into a continuous, calibrated safety score, allowing applications to threshold or rank results by confidence rather than depend on a single discrete label. This formulation unifies prompt classification, response moderation, refusal detection, toxicity detection, and multimodal safety in one interface, while letting teams adapt policies without retraining the model. Shieldstral can evaluate prompts, responses, prompt-response pairs, images, and images with accompanying text.
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