Tikos provides an AI assurance platform designed to help organizations meet regulatory compliance and technical testing requirements throughout the AI system lifecycle. Their suite of tools enables bias auditing, performance testing, and conformity assessment for AI models and systems. This platform ensures AI outputs are fair, transparent, robust, and accountable across regulated environments.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations face significant challenges in ensuring their AI systems are fair, transparent, accurate, and accountable, especially with evolving regulatory landscapes. The technical complexity of AI models and the need for continuous monitoring across the entire AI lifecycle create a gap in achieving robust AI assurance.
Solution
Tikos provides an AI assurance platform designed to integrate seamlessly into AI development and deployment pipelines, enabling organizations to build and maintain trustworthy AI systems. The platform offers a suite of tools that facilitate model and system audit, assessment, and ongoing monitoring. By addressing key capabilities such as fairness, transparency, accuracy, and accountability, Tikos helps organizations meet compliance requirements for various AI regulations and standards. The platform's technology is built on proprietary research in AI observability, reasoning, and explainability, ensuring comprehensive coverage across the AI lifecycle.
Target Audience
The primary target audience includes tech teams, GRC teams, AI developers, and AI governance professionals within organizations, particularly those in regulated sectors such as finance and healthcare, as well as government entities.
Features
- **TIKOS™ Evaluate:** For comprehensive AI model and system audit, assessment, and assurance, generating reports aligned with AI regulations.
- **TIKOS™ Explain:** Provides compliant AI model monitoring, transparency, and explainability by detailing decision outputs with contextual reasoning and data provenance.
- **TIKOS™ Explore:** A developer toolkit for building trustworthy AI systems, integrating evaluations and reliable metrics during development and testing phases.
- **Fair & Unbiased:** Tools to detect and mitigate biases in AI data and models, ensuring fair and non-discriminatory outcomes.
- **Transparent & Explainable:** Features to ensure AI systems and their outputs are transparent and clearly documented.
- **Accurate, Safe & Robust:** Capabilities to identify failure points and vulnerabilities, ensuring reliable performance and resistance to misuse.
- **Accountable:** Support for human oversight and AI governance, enabling clear reporting and contestable decision outputs.
- **Model Agnostic Architecture:** Supports all machine learning and deep learning architectures, including LLMs and GenAI models, with flexible deployment options via APIs, SDKs, and private cloud.
- **Proprietary Technology:** Built on original research in AI transparency, reasoning, and explainability, utilizing innovations like the Synapses Logger and ReduceBySQ for enterprise-scale processing.