Striven is comprehensive business management software that reduces your expenses, enhances your workflows, and simplifies daily operations. Keep your company's information unified, integrated, and actionable.
With more than 20 years of experience in Software Services, we've partnered with over 8,600 organizations across numerous industries to help them create operations that are more protected, streamlined, and beneficial to their clients.
Our mission has always centered on helping people achieve more. Today, that mission drives everything in our software. We provide clear, uncomplicated pricing options and a guarantee you won't find anywhere else. You can begin using it today without spending a dime.
None of our plans include trials, time limits, or binding contracts.
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kama.ai is a Responsible AI Agent platform that gives you an accurate, accountable, and safe AI for your organization. It is used for training, quick source of truth for compliance issues, internal support, customer service, and for specialized communities needs.
Unlike generic GenAI tools that create answers probabilistically, kama.ai combines deterministic Knowledge Graph AI with governed Generative AI and Trusted Collections. Trusted Collections is a RAG technology that minimizes generative side hallucinations, while providing a core source for accurate, brand-safe, and a correct information source for AI answers. It lets organizations control what their AI Agents know, where answers come from, and how information is delivered to employees, customers, learners, members, or community users.
kama.ai’s platform is designed for situations where answers must be accurate, traceable, brand-safe, and aligned with approved source material. Human experts and Knowledge Managers can curate content, review AI-generated drafts, manage knowledge domains, and improve responses over time. This supports a governed-in-advance approach to AI, rather than relying on after-the-fact correction.
kama.ai is especially well suited for knowledge-heavy organizations, training programs, compliance environments, Indigenous and community-focused initiatives, HR support, education, research, and other use cases where trusted information matters.
This platform focused on Responsible AI use and delivery, results in safer AI adoption, better knowledge access, reduced repetitive workload, and more consistent support for the people who rely on your organization’s expertise.
Think kama.ai for trusted AI, governed knowledge, and answers your organization is willing to stand behind.
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Gemini 4 Argon
Gemini 4 Argon is a frontier AI model from Google DeepMind built to sustain deep reasoning across complex, long-running professional workflows. Google designed the model for demanding work spanning software engineering, finance, legal tasks, enterprise knowledge work, cybersecurity defense, and creative writing. Argon supports coding, reasoning, multimodality, and multi-step task execution, allowing it to work across workflows that require information gathering, analysis, tool use, and extended problem solving. Its output token limit has been increased from 64,000 to 1 million tokens, giving the model additional capacity for lengthy reasoning and generation within a single trajectory. On DeepSWE v1.1, Google reports a score of 77.9% for real-world long-horizon software engineering, while its AutomationBench score of 51.3% measures performance on end-to-end business workflows. Google also reports strong results on evaluations covering finance, legal work, visual analysis, and long-video understanding, including a 91.7% score on LVBench. For cybersecurity teams, Argon can autonomously discover, validate, and patch software vulnerabilities and achieved a reported 68% score on CWE-bench v1. Google is initially providing the model to selected cyber defenders through its Fairwind Program while strengthening safeguards before expanding access to developers, enterprises, and consumers. Argon is planned to launch at an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input tokens receiving a 95% discount from the standard input price.
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MiniMax M3
MiniMax M3 is a frontier open-weight AI model built for coding, agentic work, multimodal understanding, and ultra-long-context tasks. The model supports up to a 1 million token context window, allowing it to work across large codebases, long documents, logs, project histories, and complex task environments. MiniMax M3 introduces MiniMax Sparse Attention, a sparse attention architecture designed to make long-context processing more efficient. The model is natively multimodal, with training that supports deeper semantic fusion across text, image, and video inputs. It is designed to support software engineering tasks, repository analysis, terminal-style work, browser-style retrieval, tool use, and autonomous workflows. MiniMax M3 has a mixture-of-experts architecture with hundreds of billions of total parameters and a smaller activated parameter count for more efficient inference. Developers can use it for AI coding assistants, workflow automation, research agents, document analysis, visual reasoning, and enterprise AI systems. Its long-context capability makes it especially useful when tasks require many files, references, instructions, or interaction histories to stay available at once. MiniMax M3 helps teams build more capable AI agents that can understand larger problems, work across multiple modalities, and execute complex tasks with stronger context awareness.
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