LM-Kit.NET serves as a comprehensive toolkit tailored for the seamless incorporation of generative AI into .NET applications, fully compatible with Windows, Linux, and macOS systems. This versatile platform empowers your C# and VB.NET projects, facilitating the development and management of dynamic AI agents with ease.
Utilize efficient Small Language Models for on-device inference, which effectively lowers computational demands, minimizes latency, and enhances security by processing information locally. Discover the advantages of Retrieval-Augmented Generation (RAG) that improve both accuracy and relevance, while sophisticated AI agents streamline complex tasks and expedite the development process.
With native SDKs that guarantee smooth integration and optimal performance across various platforms, LM-Kit.NET also offers extensive support for custom AI agent creation and multi-agent orchestration. This toolkit simplifies the stages of prototyping, deployment, and scaling, enabling you to create intelligent, rapid, and secure solutions that are relied upon by industry professionals globally, fostering innovation and efficiency in every project.
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ARGOS Identity helps compliance and operations teams verify people and review documents with two products: ARGOS ID Check and ARGOS Omni.
With ARGOS ID Check, users verify themselves in a hosted flow: they capture their ID, take a selfie and pass a liveness check, and the result arrives as approved, rejected or pending. Behind it, ID Check reads 4,000+ ID document types from 200+ countries, checks the ID for forgery, matches the face to the ID photo, screens users against sanctions and PEP lists and keeps monitoring them. Your team sets the approval thresholds and custom policy rules, and cases that need judgment go to reviewers as pending.
With ARGOS Omni, a Review Ops Agent, reviewers write their criteria in plain language. Omni turns them into a playbook and reviews each case the way the team would: it checks that the required documents are there, extracts and compares the data, screens names against AML watchlists, and returns verified, rejected or pending_review with the reason and evidence for every decision. Teams use it for business customer onboarding (KYB), vendor onboarding, corporate telecom subscription review and insurance claims.
Pricing is usage-based and quoted by sales.
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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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ScholarIQ
ScholarIQ is an innovative online research assistant powered by AI, aimed at simplifying the exploration and examination of scientific literature. It enables researchers to pose inquiries, retrieve documents from a variety of databases like OpenAlex, ORCID, and PubMed, and even import their own search results and source materials. The platform assesses articles according to defined review standards, boosts citation-based exploration through snowballing methods, and supports users in efficiently sifting through records, emphasizing relevant excerpts, and extracting needed information from uploaded files. In addition, it offers responses and suggested values that correspond to their respective citations, ensuring that reviewers retain control over decisions related to inclusion, bias assessments, and final conclusions. ScholarIQ diligently records the identities of reviewers, the justifications for their decisions, and pertinent excerpts to guarantee transparency and accountability within the review process. The tool also includes a public research metadata atlas that links various papers, researchers, journals, institutions, and topics, thereby promoting a more integrated research landscape. This comprehensive platform serves as an essential resource for both independent researchers and review teams engaged in extensive literature searches, evidence screening, and the implementation of systematic reviews, ultimately streamlining the research journey and enhancing its reliability and effectiveness. By improving collaboration and resource sharing, ScholarIQ plays a crucial role in advancing research endeavors across various scientific disciplines.
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