CompUp is an all-in-one compensation management platform designed to help rewards teams benchmark, plan, and communicate compensation to support fair pay. By bringing all compensation data and benchmarks together, it provides valuable insights for running appraisal simulations and managing executive appraisals with ease.
Core Product Modules:
Survey Management: Centralizes the handling of all compensation surveys.
Bands: Build and securely share pay bands across functions, job families, and levels.
Simulation: Conduct budget simulations to recommend employee-specific increments.
Appraisal Cycles: Streamlined multi-level budget approvals for business units.
People Analytics: Customizable dashboards offer deep insights for data-driven decisions.
Total Rewards Portal: Show employees the total value of their compensation.
Pay Equity Management: Identify and correct pay disparities to ensure compliance.
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Lofty, formerly Chime, is a platform that combines a powerful AI-powered CRM with popular tools such as our Dynamic CMA, automated social media marketing, and a stunning IDX website. It's known for its ease-of-use. Our intuitive system is designed from the ground-up for real estate professionals who want to drive more leads and close them. No matter how long your agents have worked in the industry or their level in technical skills, they can easily use Lofty to generate results.
Want an AI assistant who engages with leads 24/7, and learns from its interactions? We have that. Want a geo-farming tool that will help you find those hard-to locate seller leads in your neighborhood? We have that (it's already built-in). Want award-winning software that understands the way teams work and helps you stand out in the competition? We have all of that and more.
Want to close MORE deals FASTER? Lofty is here!
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Gemini 3.5 Flash Cyber
Gemini 3.5 Flash Cyber is a dedicated model designed specifically for cybersecurity, built upon Gemini 3.5 Flash, and refined to efficiently discover, validate, and resolve vulnerabilities at scale. Its primary objective is to support defensive security operations by enabling organizations to quickly pinpoint critical vulnerabilities and produce dependable patches before they can be exploited. The remarkable blend of performance and efficiency offered by Flash provides an excellent basis for code scanning, assessing security issues, confirming the authenticity of findings, and suggesting precise remediation strategies within extensive software environments. In the CodeMender framework, numerous Gemini 3.5 Flash Cyber agents collaborate seamlessly, merging their insights into a comprehensive report that enhances the system's ability to analyze vulnerabilities from various perspectives and elevate the overall quality of the findings. This collaborative agent framework ensures exceptional performance on CyberGym, which serves as a benchmark for assessing cybersecurity effectiveness, while also fostering continuous improvement in vulnerability management practices. Ultimately, the capabilities of Gemini 3.5 Flash Cyber not only streamline security workflows but also strengthen an organization's resilience against potential threats.
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Gemini 3.6 Flash
Gemini 3.6 Flash is Google’s workhorse Flash model for developers and enterprises building production AI agents at scale. The model is designed to deliver higher quality than Gemini 3.5 Flash while improving token efficiency, latency, and overall task cost. Google says Gemini 3.6 Flash uses 17% fewer output tokens than 3.5 Flash on the Artificial Analysis Index and can show even larger efficiency gains on certain software engineering benchmarks. It is priced lower than 3.5 Flash at $1.50 per 1 million input tokens and $7.50 per 1 million output tokens. Gemini 3.6 Flash improves performance in coding, ML research, computer use, knowledge work, document parsing, chart analysis, report drafting, and data-heavy workflows. The model also supports built-in computer use through the Gemini API and Gemini Enterprise, making it more useful for agentic systems that need to operate across digital environments. Google highlights customer use cases involving financial transcript analysis, code migrations, visual workflows, and interactive design tools. The model includes enhanced Frontier Safety safeguards for CBRN and cyber offense misuse while aiming to reduce unnecessary refusals for beneficial uses. By combining efficiency, stronger reasoning, multimodal ability, computer use, and enterprise availability, Gemini 3.6 Flash gives teams a practical model for scaling AI agents in production.
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