Seekr provides an end-to-end AI platform that utilizes patented technologies to enhance the accuracy of large language models (LLMs) while minimizing bias and errors. The platform simplifies AI development, enabling businesses to quickly build, validate, and deploy trusted AI applications tailored to their specific industry needs.
Funding
$74M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises face challenges in deploying large language models (LLMs) due to inaccuracies, biases, and the complexity of integrating various AI infrastructure components. The cost and time associated with data preparation and model validation further impede the adoption of trusted AI applications.
Solution
Seekr provides an end-to-end AI platform, SeekrFlow, designed to streamline the development, validation, and deployment of trusted AI applications. The platform enhances the accuracy of LLMs by minimizing bias and errors through patented technologies and agentic AI. SeekrFlow simplifies AI workflows by offering a unified interface accessible via API, SDK, or a no-code UI, enabling businesses to manage all their AI needs in one place. The platform's AI-Ready Data Engine allows users to customize models with their own data, improving accuracy and relevance while reducing data preparation costs.
Target Audience
The primary target audience includes enterprises across various industries (Government, Financial Services, Healthcare) looking to build, validate, and deploy trusted AI applications with improved accuracy and reduced complexity.
Features
- AI-Ready Data Engine: Customizes models using existing data, improving accuracy and relevance of base model responses.
- Agentic AI: Reduces data preparation costs by automating data generation, synthesis, augmentation, labeling, and curation.
- Confidence Scores: Troubleshoots at the token level, enabling users to validate model accuracy and detect hallucinations.
- Side-by-Side Comparisons: Compares responses from two models simultaneously for real-time evaluation of model performance.
- Five-Step Deployment: Simplifies the process of launching models into production with guided stages for inference, setup, compatibility, and autoscaling.
- Deployment Dashboard: Provides real-time visibility into metrics such as uptime, API calls, memory usage, and token counts.
- SOC-2 Compliance: Adheres to industry best practices and SOC-2 compliance standards across data storage, transit, permissions, and access.