Crono is an AI-powered sales automation platform tailored for B2B sales teams. It provides a comprehensive solution for managing leads, enhancing data with a multi-provider approach, and creating effective multichannel sequences to close deals swiftly. Crono leverages its proprietary AI model to automate daily operations, centralize data flows, and integrate with various tools such as CRMs, email providers, LinkedIn, and calling systems. This reduces manual tasks and enables sales teams to focus more on strategic decision-making.

Qantto revolutionizes the quoting process with its AI-driven automation capabilities. This platform allows businesses to generate quotes in real-time, significantly reducing the time spent on administrative tasks. By automating the quoting process, Qantto helps teams focus on closing deals rather than managing unqualified leads. This not only enhances productivity but also improves sales conversion rates by ensuring that sales teams are only pursuing qualified opportunities.

Benki offers an advanced AI platform for the financial sector, specifically targeting M&A, risk analysis, due diligence, and compliance. Users can create and customize AI agents, integrate knowledge sources, and track both AI and human contributions to ensure transparent audit trails. The platform also includes FinBench Arena for evaluating financial models and strategizing LLM deployment based on risk tolerance. This leads to faster deal closures, reduced risks, and clear audit trails, bringing confidence back to every deal.

negotiation_agent provides a modular toolkit for building autonomous negotiation bots powered by GPT-like models. Developers can specify negotiation scenarios by defining items, preferences, and utility functions to model agent objectives. The framework includes pre-defined agent templates and allows integration of custom strategies, enabling offer generation, counteroffer evaluation, acceptance decisions, and deal closure. It manages dialogue flows using standardized protocols, supports batch simulations for tournament-style experiments, and calculates performance metrics such as agreement rate, utility gains, and fairness scores. The open architecture facilitates swapping underlying LLM backends and extending agent logic through plugins. With negotiation_agent, teams can quickly prototype and evaluate automated bargaining solutions in e-commerce, research, and educational settings.