Composable vs Eyer: Which is better?

Composable is an API-first platform for building AI/LLM applications. It provides an LLM interaction design studio, prompt library, advanced LLM virtualization layer, orchestration engine, API service, executions store, analytics, QA tools and more. With fine-grained security, governance, versioning, and fine-tuning capabilities, Composable is the ideal software for enterprise teams looking to automate and augment their business processes and applications with LLM-powered tasks.

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Eyer

Eyer is an AI-powered observability and AIOps platform, designed to integrate seamlessly into existing technology stacks via APIs. The key function of Eyer is automatic identification of abnormal behavior in real-time from time-series data. It generates actionable insights which can be utilized to manually or automatically resolve identified issues. These insights are accessible through OpenAPIs, allowing a wide range of techniques for user-guided or automated response. Data integration with Eyer is facilitated through open source metrics agents like Influx Telegraf and Prometheus. Eyer's headless, cloud-based architecture enables users to nourish the platform with performance data from any system and present insights into third-party tools of their choice, like Grafana, Boomi, or Power BI. Eyer has built-in functionalities for integration with various other platforms, including Boomi and BizTalk, and supports a wide variety of other technologies through standard OpenAPIs for data ingress and egress. Feature highlights of Eyer include its automated anomaly detection capabilities, dependency mapping based on its correlation engine, and its commitment to increase system uptime and availability. It is built to provide quick value through the automation of manual tasks, the provision of actionable insights, and improvements in IT operational efficiency and system availability.

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Key features

Composable

Agentic AI Platform: A platform designed for business transformation through trusted AI agents that automate complex workflows.
Multi-Model Support: Ability to utilize various leading AI models for applications and agents, ensuring adaptability to changing AI landscapes.
Autonomous Agent Builder: A feature that allows users to quickly build and deploy autonomous AI agents within minutes.
Semantic DocPrep: A tool for preparing content for AI to enhance accuracy in results.
AI Assistant: A secure, chat-based application that enables users to interact with AI and create autonomous agents easily.

Eyer

Autonomous Fingerprint Learning: Eyer learns the operational fingerprint from time-series data, creating dynamic baselines without manual thresholds.
Cascade Intelligence: Identifies root causes of anomalies through mathematical correlation of metrics, distinguishing primary signals from cascading effects.
Early, Context-Rich Alerts: Provides actionable alerts with detailed context before thresholds are breached, including likely causes and recommendations.
Agentic AI Integration: Combines written knowledge, digital fingerprints, and live signals to support the development of maintenance and compliance agents.
Rapid Proof of Value: Delivers initial findings within one week using historical data, requiring no new sensors or infrastructure changes.

Useful for

Composable

Enables rapid development and deployment of custom AI applications using a library of shared UI components.
Streamlines complex business workflows with trusted AI agents, enhancing operational efficiency.
Supports multiple AI models, ensuring businesses can utilize the best technology available without vendor lock-in.
Provides built-in privacy and security features, reducing operational risks associated with AI implementation.
Facilitates automation of document-intensive processes, leading to faster time to value and improved customer experiences.

Eyer

Detects anomalies in time-series data before failures become visible, allowing for proactive intervention.
Utilizes autonomous fingerprint learning to establish dynamic baselines without the need for manual thresholds or new sensors.
Provides context-rich, actionable alerts that include potential causes and recommendations, enhancing decision-making.
Correlates multiple metrics to identify root causes of issues rather than just symptoms, improving operational understanding.
Adapts to specific operational dynamics, ensuring relevance across various industrial sectors without imposing generic baselines.

Use cases

Composable

Automate complex, document-intensive business workflows using trusted AI agents.
Build and deploy autonomous AI agents quickly with the Autonomous Agent Builder feature.
Enhance customer service by creating AI agents that understand context and complex queries.
Streamline data preparation and response generation with the Agentic RAG tool.
Transform enterprise content into actionable intelligence through AI-driven insights and automation.

Eyer

Early detection of anomalies in industrial operations before failures become visible.
Autonomous learning of operational behavior from time-series data without the need for new sensors or direct PLC access.
Context-rich alerts that provide actionable insights, including root cause analysis and recommendations.
Adaptation to specific operational dynamics, allowing for customized monitoring across various industries.
Utilization of historical data to identify patterns and missed monitoring opportunities, enhancing operational efficiency.

Price

Composable

Vertesia offers a SaaS platform that allows for the rapid development and deployment of agentic AI solutions at a significantly lower cost compared to traditional methods.
Customers can deploy new agentic AI apps and agents more than 10 times faster and at less than 1/10th the cost of building their own infrastructure.
The platform is designed to help organizations transform their business processes efficiently, with a focus on reducing operational costs and improving productivity.
Pricing details are not explicitly stated, but the platform is positioned as a cost-effective alternative to custom-built solutions, which can run into hundreds of thousands of dollars.
For specific pricing inquiries, potential customers are encouraged to contact Vertesia directly for personalized information.

Eyer

Proof of Value (POV) report available after analyzing historical time-series data.
First findings delivered within one week without requiring new sensors or infrastructure changes.
Eyer learns operational baselines and identifies deviations autonomously.
No integration project needed; runs solely on historical data.
Concrete report provided detailing missed patterns and recommended actions.