Deeper Insights provides a platform called Floating Point that optimizes the five key stages of AI project delivery, including model selection, data preparation, training, integration, and management. The company enables businesses to leverage AI effectively while ensuring ownership of intellectual property and adherence to responsible AI standards, addressing the challenges of deploying scalable and reliable AI solutions.
Funding
$2.4M 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
Many organizations struggle to effectively deploy and manage AI projects due to the complexity of model selection, data preparation, training, integration, and ongoing management. Businesses often lack the internal expertise and infrastructure required to navigate the vast landscape of AI models and ensure responsible AI practices. This can lead to inefficient AI implementations, wasted resources, and challenges in maintaining model accuracy and scalability.
Solution
Deeper Insights offers the Floating Point platform, a workflow optimization solution designed to streamline the five key stages of AI project delivery. The platform facilitates rapid iteration and testing of AI models, enabling businesses to identify the optimal configuration for their specific use cases. Floating Point supports both cloud and on-premise integration, allowing for flexible deployment options based on data privacy and infrastructure requirements. The platform also provides tools for continuous monitoring, data drift detection, and model retraining, ensuring long-term performance and adherence to responsible AI standards.
Target Audience
The primary target audience includes businesses across various industries, such as healthcare, real estate, and finance, seeking to leverage AI for data-driven decision-making and process optimization.
Features
- Model selection module for iterating and testing various open-source AI models and architectures.
- Data preparation tools for ingesting, processing, and annotating raw data sets.
- Model-agnostic and cloud-agnostic training environment for optimizing infrastructure.
- Integration capabilities for both cloud and on-premise deployments.
- Monitoring and management tools for tracking data drift and model accuracy.
- Automated categorization of content using Natural Language Processing (NLP).
- Scalable architecture that automatically adjusts to meet business needs.
- Compliant with ISO 27001 infosec standards and ethical AI frameworks.