Concord Horizon is an AI native contract platform built from a complete rewrite of Concord’s technology, applying ten years of experience to a modern architecture for faster and more accurate contract work.
The redesigned interface offers light and dark mode, collapsible navigation, full screen focus, custom columns, advanced filtering, and consistent tables across modules.
AI Copilot supports natural language questions, contract summaries, key point extraction, and fast portfolio insights, while AI Search adds lexical and semantic search with improved performance and multi actions on results.
MCP brings contract intelligence into AI tools like ChatGPT and Claude for summaries, tables, or automated monitoring. Concord applies a strict zero data retention policy with AI partners and never uses customer data to train AI models .
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An AI based accessibility tool enables websites to be accessible among people with hearing or vision impairments, motor impaired, color blind, dyslexia, cognitive & learning impairments, seizure & epileptic, ADHD, elderly, and Parkinson. It installs in just 2 minutes. It reduces the risk of time-consuming accessibility lawsuits by improving accessibility compliance for the standards WCAG 2.0, 2.1, 2.2, ADA, Section 508, European EAA EN 301 549, Canada ACA, California Unruh, Israeli Standard 5568, Australian DDA, UK Equality Act, Ontario AODA, Indian RPD Act, GIGW 3.0, France RGAA, German BITV, Brazilian Inclusion law LBI 13.146/2015, Spain UNE 139803:2012, JIS X 8341, Italian Stanca Act, Switzerland DDA & more. It supports GDPR, HIPAA, CCPA, SOC Type 2, ISO 9001:2015, & ISO 27001:2022.
It supports 190+ languages. It is a cornerstone of improving web accessibility through its ease of use for companies of all sizes and with the help of paid add-ons like manual accessibility audit, remediation, PDF accessibility remediation, VPAT/ ACR, white label subscription, and live site translation, SkynetAccessibility Scanner, and video subtitle.
Top features of the All in One Accessibility:
- AI Screen Reader
- Accessibility statement
- Accessibility interface for UI design fixes
- Free Accessibility Statement Generator
- Voice Navigation
- Talk & Type
- Libras (Brazilian Portuguese) Sign Language
- Dashboard Automatic accessibility score
- AI based Image Alternative Text remediation
- AI based Text to Speech Screen Reader
- Select Screen Reader Voice
- Auto-detect language
- Keyboard navigation adjustments
- Content, Color, Contrast, Orientation Adjustments
- Custom widget color, position, icon size, type
- Dedicated support
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Cognitive Workbench
ExB's AI and ML Driven Cognitive Process Automation platform allows insurance companies convert any type of text into actionable insights and information for input management and process automatization. Insurance companies can use pre-trained policies management, claims management, and text mining in reports. They can also request that we train ad-hoc models to fit their business workflows.
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SWE-2
SWE-2 is a software engineering model from Cognition built for agentic coding tasks that require strong performance at lower computational and monetary cost. It is post-trained from the Kimi K3 base model and extends Cognition’s earlier SWE-1.7 training approach with a new reinforcement learning method for jointly optimizing multiple reasoning-effort settings. Medium, high, and maximum effort modes provide different tradeoffs between speed, cost, exploration, and verification depending on task complexity. The model is trained to inspect only the parts of a codebase that are likely to matter, helping it reach implementation faster and reduce unnecessary exploration. SWE-2 can generate and modify code, run tests, analyze repositories, work through terminal tasks, and verify whether implementations satisfy user requirements. Cognition also reports improvements in end-to-end test creation, regression detection, instruction following, and re-deriving conclusions when challenged. Its training process incorporates cost-aware rewards, length-weighted reward baselines, expanded reinforcement learning environments, and hardened verifiers intended to improve both efficiency and reliability. SWE-2 is positioned as a cost-efficient alternative to larger frontier coding models while remaining competitive on software engineering benchmarks such as FrontierCode, DeepSWE, and Terminal-Bench. The model is available in Devin Desktop and Devin CLI and is being introduced to additional Cognition products including Devin Web and Fusion.
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