Coevera is an AI-native CRM and sales process platform for B2B sales organizations of 15 to 2,500 quota-carrying sellers — companies with a defined sales process, managers accountable for pipeline, and deals won through consultation rather than transaction. Formerly Pipeliner CRM, building sales software since 2011.
Results that speak for themselves: 4 weeks to implement. 0 full-time admins required. 2 hours to onboard a user. Dramatically reduced total cost of ownership.
Sales leaders get a forecast they can defend. Sales ops configure it themselves. Reps get a pipeline where the next step is obvious.
• Voyager AI: predictive deal and pipeline guidance, plus native MCP
• Visual pipelines with buying centers and relationship maps
• Guided selling: your stages and criteria, enforced in the flow of work
• Automatizer: no-code workflow automation your team builds
• Built-in reporting and forecasting, with BI export
Three editions: $85, $115 and $150 per user/month. Industry-agnostic.
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Gemini Enterprise Agent Platform is an advanced AI infrastructure from Google Cloud that enables organizations to build and manage intelligent agents at scale. As the evolution of Vertex AI, it consolidates model development, agent creation, and deployment into a unified platform. The system provides access to a diverse library of over 200 AI models, including cutting-edge Gemini models and leading third-party solutions. It supports both low-code and full-code development, giving teams flexibility in how they design and deploy agents. With capabilities like Agent Runtime, organizations can run high-performance agents that handle long-duration tasks and complex workflows. The Memory Bank feature allows agents to retain long-term context, improving personalization and decision-making. Security is a core focus, with tools like Agent Identity, Registry, and Gateway ensuring compliance, traceability, and controlled access. The platform also integrates seamlessly with enterprise systems, enabling agents to connect with data sources, applications, and operational tools. Real-time monitoring and observability features provide visibility into agent reasoning and execution. Simulation and evaluation tools allow teams to test and refine agents before and after deployment. Automated optimization further enhances agent performance by identifying issues and suggesting improvements. The platform supports multi-agent orchestration, enabling agents to collaborate and complete complex tasks efficiently. Overall, it transforms AI from a productivity tool into a fully autonomous operational capability for modern enterprises.
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Yardi Voyager
Yardi Voyager is an all-encompassing, web-based solution that integrates seamlessly and allows mobile access, specifically designed for managing large property portfolios with efficiency in operations, leasing management, data analytics, and providing advanced services for residents, tenants, and investors. This versatile platform boasts a premier suite of products that service a wide range of real estate sectors, including commercial properties like offices, retail, and industrial units, along with multifamily residences, affordable housing, senior living facilities, public housing authorities, and accommodations for military personnel, ensuring a centralized database that fulfills the entire spectrum of property management and accounting needs. By streamlining workflows and improving system-wide transparency, Voyager enables users to collaborate effectively and enhances overall productivity. Accessible from any web browser or mobile device, the platform ensures that users can quickly access vital data, facilitating prompt and informed decision-making. Moreover, as a Software as a Service (SaaS) offering, it minimizes the complexities associated with software maintenance, allowing businesses to focus on growth and operational improvement. In summary, Yardi Voyager not only simplifies property management tasks but also plays a crucial role in propelling success within the real estate landscape, making it an invaluable tool for professionals in the industry.
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voyage-code-3
Voyage AI has introduced voyage-code-3, a cutting-edge embedding model meticulously crafted to improve code retrieval performance. This groundbreaking model consistently outperforms OpenAI-v3-large and CodeSage-large by impressive margins of 13.80% and 16.81%, respectively, across a wide array of 32 distinct code retrieval datasets. It supports embeddings in several dimensions, including 2048, 1024, 512, and 256, while offering multiple quantization options such as float (32-bit), int8 (8-bit signed integer), uint8 (8-bit unsigned integer), binary (bit-packed int8), and ubinary (bit-packed uint8). With an extended context length of 32 K tokens, voyage-code-3 surpasses the limitations imposed by OpenAI's 8K and CodeSage Large's 1K context lengths, granting users enhanced flexibility. This model employs an innovative Matryoshka learning technique, allowing it to create embeddings with a layered structure of varying lengths within a single vector. As a result, users can convert documents into a 2048-dimensional vector and later retrieve shorter dimensional representations (such as 256, 512, or 1024 dimensions) without having to re-execute the embedding model, significantly boosting efficiency in code retrieval tasks. Furthermore, voyage-code-3 stands out as a powerful tool for developers aiming to optimize their coding processes and streamline workflows effectively. This advancement promises to reshape the landscape of code retrieval, making it a vital resource for software development.
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