Shram
Shram is a workforce management tool that helps companies streamline employee scheduling, track attendance, and manage payroll, enhancing operational efficiency and workforce productivity.
Shram is an AI-powered work management platform that optimizes team productivity by automating task allocation, balancing workloads, and tracking performance through intelligent insights and gamification. Its core value proposition lies in transforming routine work into an engaging experience, fostering joy, transparency, and autonomy in decentralized teams while preventing burnout and boosting collaboration.[1][2][3] Key features include AI-driven task matching based on employee availability and skills, real-time analytics dashboards, conversational AI for quick insights and auto-filling details, RPG-style progress tracking with XP and badges, and integrated communication tools.[1][2][3][4]
Designed for project managers, scrum masters, engineering teams, design groups, and mid-sized to large organizations—especially distributed or creative teams—Shram excels in use cases like team task management, performance analytics, and project progress gamification.[1][3] What sets Shram apart is its delightful, minimal interface combined with gamification elements that reward real accomplishments, GPT-powered automation for seamless workflows, and a strong emphasis on data security through cloud storage and daily backups, making it notably more motivational than traditional tools.[2][3][4]
The ToS does not explicitly address whether user data is used to train AI models. The document mentions 'service improve
The ToS does not explicitly address whether user data is used to train AI models. The document mentions 'service improve
Moderate risk. Suitable for internal data but avoid confidential information.
The ToS does not explicitly address whether user data is used to train AI models. The document mentions 'service improvement' implicitly through general service provisions but lacks clear language on AI training, opt-out mechanisms, or differentiation between free and paid tiers regarding data usage for model training.
“Not found in documents”
The ToS states users bear responsibility for content they create but does not clearly define the scope of license granted to Shram or restrictions on sublicensing. Language is vague regarding whether Shram retains rights to user-generated content beyond service delivery.
“[ToS] 'You bear full responsibility for any content you create, transmit, or publish using Shram's services.'”
The ToS mentions third-party applications and interaction with them but does not provide detailed information about data sharing with sub-processors, affiliates, or partners. No sub-processor list or Data Processing Agreement is referenced in the provided documents.
“[ToS] 'Shram's services may interact with third-party applications, for which separate terms may apply.'”
The ToS addresses inactive account termination (30 days) with prior notice and opportunity to back up data, but lacks specific retention periods for active accounts, deletion timelines, or clarity on backup data retention. Language is vague regarding overall data lifecycle.
“[ToS] 'Shram reserves the right to terminate accounts that remain inactive for an extended period (e.g., 30 days). Prior notice will be given before any termination, and you will be given the opportunity to back up your data.'”
The ToS assigns responsibility for user-generated content to the user but does not explicitly state whether the company retains ownership of outputs or whether Shram claims any license rights to generated content. Ownership language is ambiguous.
“[ToS] 'You bear full responsibility for any content you create, transmit, or publish using Shram's services.'”
The provided ToS document contains no mention of SOC 2, ISO 27001, GDPR compliance, HIPAA, or any security certifications. No Data Processing Agreement, trust page, or security documentation is referenced or linked.
“Not found in documents”
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