
Synap is a smart online exam platform designed to create, deliver, and manage secure, question-based assessments. Trusted by educational institutions and organisations worldwide, Synap supports a wide range of exam types, from practice tests to high-stakes, proctored exams.
The platform offers a user-friendly interface for creating comprehensive assessments with diverse question formats, including images, multiple-choice questions (MCQs), and extended matching questions (EMQs). Questions can be built directly on the platform or imported in bulk via CSV, enabling efficient large-scale exam creation.
Synap’s integrated proctoring service ensures exam integrity by monitoring candidates during live exams, preventing cheating and fraud. Flexible exam settings include timers, randomisation, and secure browsers, all designed to maintain a fair testing environment.
Robust analytics and reporting tools provide detailed insights into candidate performance, question effectiveness, and overall exam outcomes. These insights help educators and organisations identify knowledge gaps, optimise assessments, and improve learner outcomes.
With full portal customisation and seamless LMS integrations, Synap offers a scalable solution suitable for small teams to enterprise-level clients. Supported by API access and dedicated customer service, Synap streamlines exam workflows and empowers organisations to deliver high-quality, secure exams with ease.
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AuthorityTech operates the world’s inaugural AI-native Machine Relations platform and agency, engineered specifically to establish ambitious brands within the Tier-1 media outlets that AI search engines intuitively trust, index, and cite. While legacy public relations agencies rely on retainer-heavy efforts to influence humans, AuthorityTech designs earned media for the true modern gatekeeper—the machine—utilizing a risk-free, 100% performance-based, pay-per-placement framework. Through this approach, leading answer engines like ChatGPT, Perplexity, Gemini, and Google AI Overviews can accurately process the brand, map its placement to the correct market category, and reference it during high-intent buyer queries.
Defined in 2024 by Founder and CEO Jaxon Parrott, Machine Relations represents the strategic discipline of making corporate brands discoverable and citable across LLM architecture. AuthorityTech executes this via a proprietary five-layer system: Earned Authority, Entity Clarity, Citation Architecture, Distribution, and Measurement—unifying AI SEO, GEO, AEO, and PR into a singular engine for scaling machine trust.
Chief Growth Officer and Cofounder Christian Lehman operationalizes the methodology, collaborating directly with growth companies to deploy this strategy globally. Tapping into a direct distribution network of over 1,600 Tier-1 publications, AuthorityTech has generated thousands of AI-cited placements for more than 200 corporate clients, including 27 tech unicorns, to secure permanent AI search footprint and measurable citation share.
The agency delivers this through a three-stage execution process:
Map: Reverse-engineering category landscapes and competitor prompt footprints.
Match: Blending unique brand narratives with highly authoritative media outlets.
Place: Guaranteeing live coverage through strategic, relationship-driven outreach.
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Agent Bayes
Agent Bayes is an AI-powered research assistant specifically designed for graduate students, postdoctoral researchers, and academics. Users can easily upload their articles in PDF format or connect their Zotero libraries to the platform, enabling them to ask questions about their gathered materials. The assistant expertly navigates through these documents, creating a mindmap that outlines various claims, each linked to the corresponding passage and page number that supports it. Users can interact with the citations, clicking to access the relevant excerpts or PDF pages, which allows for a visualization of competing research perspectives as separate, sourced viewpoints. Furthermore, the AI Verification feature checks if the cited passages sufficiently back up a claim, although this functionality is exclusive to those with paid subscriptions. An MCP server supports the integration of compatible tools like Claude Code, Codex, and Cursor, allowing these tools to search the user’s library and utilize the answers and mindmaps derived from the citations. The free tier provides users with 50 credits per month, while paid plans begin at $11 per month, billed annually, offering a variety of options to enhance users' research journeys. Ultimately, this cutting-edge assistant is designed to simplify the research process, fostering greater efficiency and productivity in academic endeavors. With its user-friendly interface and sophisticated features, Agent Bayes represents a significant advancement in academic support technology.
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NeuralVerge
NeuralVerge is an innovative AI-powered platform designed for research and data extraction, specifically aimed at go-to-market, compliance, and research teams, along with the AI agents they create. Users can pose simple questions or target inquiries at a specific business, person, or website, receiving organized responses with accurate citations for every piece of information.
The AI Research feature adeptly decomposes intricate questions into smaller, manageable sub-queries, effectively routing them to suitable sources at once and merging the findings into a single, thoroughly cited answer. At the same time, AI Extract converts any webpage or document into well-structured JSON following user-specified schemas, thus removing the necessity for constant selector maintenance.
With access to a comprehensive network of 29 data sources under a unified request format, the platform provides insights into company intelligence, 12 corporate registries, contact enhancement, and publicly accessible social media profiles. This extensive functionality is easily available through a web application, REST API, or as an MCP server, allowing both analysts and AI agents to work together seamlessly within the same data pipeline.
The pricing model is based on a points system beginning at $20 per month, with no additional fees for individual users, enabling potential customers to try the service without providing credit card information. This offers teams a risk-free opportunity to explore the platform's capabilities without immediate financial obligations, fostering greater experimentation and adoption.
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