C3.ai - Detailed Review
App Tools
C3.ai - Product Overview
C3.ai Overview
C3.ai is a leading provider of Enterprise AI software, designed to accelerate digital transformation across various industries. Here’s a brief overview of its primary function, target audience, and key features:
Primary Function
C3.ai’s primary function is to enable businesses to develop, deploy, and operate enterprise-scale AI applications efficiently and cost-effectively. The platform is built to address specific business problems such as predictive maintenance, fraud detection, supply network optimization, energy management, and customer engagement.
Target Audience
The target audience for C3.ai includes large organizations and enterprises across multiple industries, such as manufacturing, finance, healthcare, government, and utilities. Companies like Shell, Bank of America, the U.S. Air Force, Koch Industries, and ENGIE are among its notable clients.
Key Features
C3 AI Platform
This is the core platform that provides a model-driven architecture for developing and deploying AI applications. It allows for the development of enterprise AI applications 25 times faster with 95% less code compared to alternative methods.
C3 AI Type System
This is a data object-centric abstraction layer that integrates various platform components, enabling interoperability between different programming languages, computational models, and infrastructure services. It simplifies the development process by abstracting underlying physical data models and infrastructure services.
Pre-built Applications
C3.ai offers a range of pre-built AI applications for common industry problems, such as predictive maintenance, inventory optimization, and customer relationship management. These applications can be quickly implemented to address specific business needs.
C3 AI Ex Machina
This is a no-code solution that allows non-programmers to leverage AI for data analysis and model building, making AI accessible to a broader range of users.
Integration and Interoperability
The platform supports multiple programming language bindings (Java, JavaScript, Python, Scala, and R) and provides RESTful interfaces for interoperability with external systems.
Advanced AI and Optimization
C3.ai combines AI and optimization algorithms to tackle complex problems, such as dynamic probabilistic forecasts and constraint programming, as seen in its inventory optimization solutions.
Overall, C3.ai is focused on delivering immediate value to its customers by providing a comprehensive set of tools and services that simplify the development and deployment of AI applications, thereby driving innovation and efficiency across various industries.
C3.ai - User Interface and Experience
User Interface of C3.ai
The user interface of C3.ai, particularly in its App Tools AI-driven product category, is built to be highly engaging, intuitive, and efficient. Here are some key aspects of its user interface and overall user experience:
UI Framework and Components
C3.ai provides a common UI framework that includes a rich component library with over 100 layout, workflow, and user interface components. These components are optimized for performance, offer flexible customizations for theming, and support translations. This framework allows developers to easily configure and connect these components to underlying data and analytics, making application development more streamlined.
Visualization and Customization
The platform includes a library of visualization components such as line and bar charts, scatter plots, histograms, and geospatial maps. These components can be used to build custom UI or extend existing applications with rich visualizations on a drag-and-drop development canvas. This high level of customization and flexibility enhances the user experience by providing clear and insightful data visualizations.
Third-Party Integration
C3.ai supports the integration of third-party libraries and frameworks, such as React, allowing developers to leverage existing UI investments. This feature ensures that the platform is versatile and can adapt to various development needs, making it easier for users to incorporate familiar tools into their workflow.
Collaboration and Reusability
The C3 AI Platform is structured to facilitate collaboration among different teams by enabling them to work on the same codebase. It promotes the reusability of software components, APIs, data, and AI pipelines, which significantly reduces the time and cost associated with building applications for additional use cases. This collaborative environment enhances productivity and ensures that users can build upon each other’s work without starting from scratch.
Development Experience
Version 8 of the C3 AI Platform introduces a re-architected AI Studio that serves as a unified experience for all personas, including developers, data scientists, and operations teams. This studio provides a declarative configuration experience, enhanced VS Code extensions for writing and managing tests, and a DevOps Studio for building, managing, and deploying applications. The platform supports both deep code and low-code/no-code development models, catering to different user preferences and skill sets.
Ease of Use
The platform is designed to be user-friendly, with features like single sign-on integration and the ability to deploy applications with minimal human intervention. For example, once the initial application is set up, subsequent applications can be deployed quickly, often within minutes, without requiring extensive IT involvement. This ease of use makes the platform accessible and efficient for a wide range of users.
Summary
In summary, the C3.ai user interface is characterized by its intuitive and flexible components, strong support for visualization and customization, seamless integration with third-party tools, and a collaborative environment that enhances productivity. The overall user experience is streamlined, efficient, and adaptable to various development needs.
C3.ai - Key Features and Functionality
The C3 AI Platform
The C3 AI platform is a comprehensive suite of tools and services that revolutionize enterprise-scale AI application development. Here are the main features and their functionalities:
Data Integration
C3 AI’s data integration capabilities are crucial for unifying disparate data sources. Here’s how it works:
- Connectors: The platform includes over 200 connectors to integrate data from various enterprise and external databases, tools, and applications, ensuring seamless access to both structured and unstructured data.
- Canonicals: Data engineers can use pre-built canonical data models or create custom connections to load data directly into the C3 AI Platform, allowing for flexible data loading.
- Transformations: With over 200 pre-built data transformations, data preparation is accelerated. These transformations can be customized using Python or JavaScript and include functions like aggregations, window functions, text manipulation, and anomaly detection.
- Storage: The platform supports multi-database persistence, including key-value stores, NoSQL storage, RDBMS, and distributed file systems, ensuring effective storage and management of data.
- Virtualization: Data virtualization eliminates the need for data duplication by creating virtual unified data images, which helps in optimizing compute workloads and enabling near real-time analytics.
- Streaming Data: C3 AI integrates and processes streaming data from various sources, including Apache Kafka, AWS Kinesis, and Azure EventHub, enabling near real-time analytics and model inference.
Feature Store
The Feature Store is a central hub for managing machine learning features:
- Feature Registry: This registry allows users to find, define, and incorporate features easily, promoting standardization and collaboration across teams. It includes cataloging and search capabilities to accelerate model and application development.
- Feature Creation: Users can define and store features along with their associated metadata. Over 200 pre-built functions aid in experimentation and application development, promoting feature reusability.
- Feature Serving: The platform separates data pipelines from ML models, ensuring that features are served to models with up-to-date data, making predictions timely and relevant.
- Feature Lineage: This feature documents the relationships between features, models, and data snapshots, enabling model and experiment reproducibility at scale.
Model-Driven Architecture
C3 AI uses a model-driven development approach:
- This architecture allows for seamless prototyping and rapid production deployments. It supports an impressive 1.8 billion predictions per day, indicating its scalability and efficiency.
Pre-built AI Applications
C3 AI offers a wide range of pre-built applications:
- With over 90 pre-built enterprise AI applications, the platform addresses various industry-specific use cases, significantly reducing development time and costs. These applications cover industries such as energy, manufacturing, financial services, and more.
Multi-Cloud Compatibility
The platform is designed to run across multiple cloud environments:
- It abstracts cloud-specific capabilities, allowing users to exploit them in their native form. This ensures flexibility and compatibility with different cloud infrastructures.
AI-First Design
C3 AI’s architecture is open and AI-first:
- This design integrates natively with existing data and ML investments, providing a unified workspace across the AI lifecycle. It supports both no-code/low-code and full-code development options, catering to a wide range of users from business analysts to data scientists.
C3 AI Type System
The C3 AI Type System is a data object-centric abstraction layer:
- It binds various platform components, including infrastructure and services, allowing developers and data scientists to access the platform, virtual data lake, applications, and microservices through RESTful interfaces and multiple programming language bindings (Java, JavaScript, Python, Scala, and R).
- The Type System enables interoperability between different programming languages and computational models without requiring knowledge of the underlying physical data models. It supports multiple object inheritance and automatic processing of data changes through implicit dependencies.
Data Quality and Management
C3 AI emphasizes data quality and management:
- The platform improves data accuracy, completeness, consistency, and timeliness. For example, it can achieve up to 90% accuracy, 85% completeness, 95% consistency, and 88% timeliness in data quality.
- The C3 AI Data Studio provides visual tools to ingest and unify disparate data, enabling the design and exploration of data sources and structures. This ensures that data is ready for analysis and integration into AI applications.
These features collectively enable enterprises to develop, deploy, and operate AI applications efficiently, leveraging advanced machine learning techniques and ensuring high data quality and integration.
C3.ai - Performance and Accuracy
Evaluating the Performance and Accuracy of C3.ai
Performance and Accuracy
C3.ai demonstrates high performance and accuracy in various enterprise applications. Here are some notable achievements:High-Precision Information Retrieval
C3 AI’s approach to information retrieval is highly precise, especially when dealing with multi-domain data sources. It uses state-of-the-art methods for semantic matching and robust information extractors to parse and chunk passages from various documents. This approach significantly reduces hallucinations by ensuring the model has appropriate evidence when generating results.Accuracy in Specific Use Cases
In a business intelligence and analysis use case for a large agricultural firm, C3 Generative AI achieved almost 90% accuracy on complex questions nested in dense tabular content in PDFs. Similarly, in a manufacturing application, C3 AI configured a RAG pipeline that achieved more than 90% accuracy, outperforming OpenAI’s ChatGPT, which achieved only 37% accuracy on the same questions.Automated Evaluation Framework
C3 AI employs a rigorous automated evaluation framework with three feedback loops to assess model accuracy. This includes automated ML metrics, ground truth measurements, and self-evaluation by the large language model (LLM) with periodic human calibration. This framework helps identify errors in both the retrieval and generative components of the system.Domain-Specific Insights
C3 Generative AI delivers high-accuracy, domain-specific insights across disparate enterprise and external data sources. It supports various data types, including documents, tables, sensor telemetry, and images, enabling faster, data-driven decisions.Limitations and Areas for Improvement
While C3.ai shows impressive performance, there are a few areas that could be improved or require careful consideration:Model Tuning and Configuration
Although C3 AI’s retrieval performance is often optimized, further tuning of the generator configuration may be necessary in some deployments. This involves prompt engineering and testing different decoding strategies to maximize the success of the LLM generator.Handling Unanswerable Questions
While C3 AI RAG performs well in identifying questions it cannot answer, there is still room for improvement. For instance, in a benchmark with 20 curated unanswerable questions, the model correctly identified it could not answer 18 of them, but there is always potential to improve this further.Continuous Monitoring and Maintenance
To maintain high accuracy and performance, C3 AI requires continuous monitoring. The platform provides tools to track model performance, set up alerts for data drift and accuracy drops, and ensure models remain reliable over time. This ongoing maintenance is crucial to prevent degradation in model performance.Engagement and User Experience
C3.ai is designed to be user-friendly and efficient:User-Friendly Interface
Deploying AI models with C3 AI is straightforward, with support for both batch and streaming data processing. The platform offers a collaborative multi-functional environment through C3 AI Studio, which includes deep code, low code, and no code development tools.Real-Time Predictions
Models can be deployed as RESTful APIs, making them accessible for real-time predictions. This enhances the overall user experience by providing quick and reliable responses to inquiries. In summary, C3.ai’s performance and accuracy are highly commendable, particularly in domain-specific applications. However, ongoing model tuning, continuous monitoring, and addressing unanswerable questions remain important areas to focus on for further improvement. C3.ai - Pricing and Plans
The Pricing Structure of C3 AI
The pricing structure of C3 AI has undergone significant changes to align with prevalent cloud usage models, particularly shifting from a subscription-based model to a consumption- or usage-based model.
Pilot Phase
- The new approach starts with a 6-month pilot subscription.
- This includes one AI Enterprise application.
- Unlimited use of the C3 AI Platform.
- Unlimited developer and runtime licensing.
- Concierge technical support and training.
Post-Pilot Pricing
- After the pilot phase, the pricing is based on consumption.
- The cost is $0.55 per vCPU hour or vGPU hour.
- This model allows for on-demand scaling of the application in production.
Key Features
- Unlimited Resources: During the pilot and post-pilot phases, customers have access to unlimited developer and data scientist seats.
- Technical Support: Concierge technical support and training are included in the pilot phase.
- Scalability: The application can be scaled on an on-demand basis post-pilot.
No Free Options
- There are no free options available for the C3 AI Suite. The minimum commitment is a 6-month pilot phase at $500,000, which includes various resources and support.
Enterprise Pricing
- For additional services or enterprise pricing, customers need to contact C3 AI directly, as these details are not publicly listed.
This new pricing model is designed to align with customer expectations and the broader SaaS market, making it more flexible and adaptable to current economic conditions.
C3.ai - Integration and Compatibility
The C3 AI Platform
The C3 AI Platform is engineered to facilitate seamless integration with a wide range of tools, databases, and platforms, ensuring broad compatibility and flexibility.
Data Integration
The C3 AI Platform comes equipped with over 200 connectors to integrate disparate data sources from enterprise and external databases, tools, and applications. This allows data engineers and scientists to unify structured and unstructured data from various sources, ensuring consistent integration across diverse data types.
Canonical Data Models and Transformations
Data engineers can use prebuilt canonical data models or create custom connections to load data directly into the C3 AI Platform. The platform also offers over 200 pre-built data transformations, which can be customized using Python or JavaScript, facilitating data preparation and ensuring compatibility with different data formats.
Multi-Platform Deployment
The C3 AI Platform supports deployment across various environments, including on-premise, cloud-native, and hybrid-cloud setups. It is compatible with major cloud providers such as Google, Microsoft, Amazon, Nvidia, Intel, OpenShift, and Hewlett-Packard Enterprise. This flexibility ensures that AI applications can be deployed in a way that meets specific security, compliance, and infrastructure requirements.
Edge and Streaming Data Integration
The platform integrates seamlessly with edge technologies and popular streaming systems like Apache Kafka, AWS Kinesis, and Azure EventHub. This enables real-time data processing, model training, and inference, even at the edge, while adhering to security and network constraints.
Data Virtualization
C3 AI’s data virtualization capabilities allow organizations to leverage existing data and machine learning investments without duplication. Developers can create virtual unified data images, infer metadata from source schemas, and optimize compute workloads, all while maintaining compatibility with various data sources and analytics tools.
Programming Language Support and Interoperability
The C3 AI Type System provides a data object-centric abstraction layer that allows programs, algorithms, and data structures written in different programming languages (such as Java, JavaScript, Python, Scala, and R) to interoperate. This system offers RESTful interfaces and programming language bindings, ensuring compatibility with a wide range of development tools and external systems.
Multi-Tenant and Sandbox Environments
The platform supports a multi-tenant development environment, where each developer can work in their own sandbox. This setup accelerates application development while maintaining security and cost efficiency, ensuring that different teams can work independently without compatibility issues.
Conclusion
In summary, the C3 AI Platform is highly adaptable and compatible across various platforms, tools, and devices, making it an effective solution for integrating and managing diverse data sources and AI applications.
C3.ai - Customer Support and Resources
Customer Support and Services Team
The Customer Support and Services team at C3 AI is dedicated to providing expert guidance and support throughout the implementation and ongoing use of AI applications. This team focuses on delivering strategic solutions, resolving customer inquiries, and enhancing the overall user experience. They work to facilitate seamless adoption and maximize the value of C3.ai’s innovative technology for enterprises.
Generative AI for Contact Centers
C3.ai’s Generative AI for Contact Centers is a key component of their customer support offerings. This solution handles routine tasks, routes calls efficiently, and generates call summaries, freeing agents to focus on complex and high-value interactions. It provides instant, accurate support by surfacing relevant information from knowledge bases, FAQs, and past interactions. The AI also simplifies self-service experiences through intuitive virtual agents and chatbots that understand natural language and offer personalized solutions.
Automated Support and Self-Service
C3 Generative AI automates routine tasks, such as answering frequently asked questions and providing troubleshooting steps, without the need for human intervention. This automation reduces wait times and helps customers resolve problems on their own. The AI-powered virtual agents and chatbots guide customers through self-service experiences, making it easier for them to find solutions without agent assistance.
Proactive Issue Identification
The AI analyzes call transcripts and customer data in real time to identify trends and potential issues, allowing for proactive outreach and resolution. This proactive approach helps in anticipating customer needs before they become significant problems.
Data-Driven Insights
C3 Generative AI provides valuable insights into customer sentiment, agent performance, and operational trends through its AI-powered analytics engine. This transforms raw data into actionable recommendations for continuous improvement, helping customer service teams to focus on the right customers, information, and pain points.
Training and Onboarding
The AI solution accelerates the learning curve for new agents by providing immediate access to comprehensive training materials, call scripts, and best practices. This ensures that agents are confident and effective from their first day on the job.
Access to Enterprise Data
C3 Generative AI for Customer Service acts as a unified knowledge source, enabling customer service teams to quickly locate, retrieve, and act on enterprise data and insights through an intuitive search and chat interface. It integrates with CRMs, customer service data, training collateral, and other siloed data sources, making it easier to access customer-specific information and promote knowledge sharing.
By leveraging these features, C3.ai ensures that customer service teams can deliver efficient, accurate, and personalized support, enhancing overall customer satisfaction and operational efficiency.
C3.ai - Pros and Cons
Main Advantages of C3.ai
C3.ai offers several significant advantages that make it a compelling choice for enterprises looking to develop, deploy, and manage AI applications:Comprehensive AI Solutions
C3.ai provides a wide range of AI solutions that address various business challenges, including predictive maintenance, fraud detection, supply chain optimization, and customer engagement. These pre-built applications can be quickly deployed to solve specific business problems.Scalable Architecture
The platform boasts a scalable architecture that allows for the integration of data from multiple sources, such as databases, data warehouses, cloud storage, and IoT devices, into a unified data lake. This ensures comprehensive data analysis and model building.Advanced Machine Learning and AI Tools
C3.ai offers advanced machine learning and AI tools, including built-in algorithms and the ability to import custom models from popular frameworks like TensorFlow, PyTorch, and Scikit-Learn. Automated machine learning (AutoML) features streamline the model training process, supporting both supervised and unsupervised learning.User-Friendly Interface and Development Tools
The platform features a user-friendly interface and development tools that make it accessible for both data scientists and business users. It supports coding in multiple languages, such as Python and R, and provides visual tools for data exploration, model building, and evaluation.Real-Time Deployment and Monitoring
Deploying AI models on C3.ai is straightforward, with the option to deploy models as RESTful APIs for real-time predictions. The platform also offers robust monitoring tools to track model performance, including alerts for data drift and accuracy drops.Collaboration and Reusability
C3.ai enhances collaboration by allowing different teams to work on the same codebase, building highly configurable, reusable, and integrated software components. This leads to significant productivity gains and reduces the cost and time to build applications for additional use cases.Strong Security and Compliance
The platform ensures strong security and compliance measures, which are crucial for enterprises handling sensitive data.Main Disadvantages of C3.ai
While C3.ai offers numerous benefits, there are some potential drawbacks to consider:Dependency on the Platform
To fully utilize AI models developed on C3.ai, organizations must maintain the entire platform architecture. If you only purchase the ML models and try to run them on a different environment, you would need to recreate the whole data pipeline and infrastructure, which can be cumbersome.Cost and Pricing
Evaluating the cost of C3.ai requires careful consideration of the organization’s needs, including the scale of deployment, the number of users, and the specific AI capabilities required. While the platform offers long-term discounts and optimization options, the initial investment can be significant.Learning Curve
Although C3.ai provides extensive support resources, including documentation, tutorials, and community forums, there may still be a learning curve for teams unfamiliar with the platform’s tools and methodologies. This could require additional time and resources for training and onboarding. In summary, C3.ai is a powerful tool for enterprises aiming to scale their AI applications, but it does come with some considerations regarding dependency on the platform, cost, and the potential learning curve for new users. C3.ai - Comparison with Competitors
When comparing C3.ai with its competitors in the AI-driven product category
Several key aspects and unique features come to the forefront.
Unique Features of C3.ai
Feature Store
Feature Store: C3 AI offers a centralized Feature Store that streamlines model development by allowing users to store, reuse, and share machine learning features. This includes a feature registry, over 200 pre-built functions for feature creation, and the ability to serve ML models with up-to-date data.
C3 AI Type System
C3 AI Type System: This is a data object-centric abstraction layer that enables programs, algorithms, and data structures written in different programming languages to interoperate seamlessly. It simplifies the development and deployment of AI, big data, and predictive analytics applications by abstracting underlying physical data models and infrastructure.
Turnkey Enterprise AI Applications
Turnkey Enterprise AI Applications: C3 AI provides over 130 ready-to-use enterprise AI applications across various sectors such as manufacturing, financial services, government, and more. These applications are designed to meet business-critical needs and can be deployed quickly.
Visualization Capabilities
Visualization Capabilities: The platform offers highly configurable geospatial visualizations, time-varying graphs, and statistical analysis tools. These features enable deep data exploration and investigative analysis, and users can integrate these visualizations with business intelligence platforms like Microsoft Power BI and Tableau.
Potential Alternatives and Competitors
SparkCognition
SparkCognition: This company specializes in AI solutions across sectors like energy, manufacturing, and government. Unlike C3 AI, SparkCognition focuses more on specific industry verticals and offers solutions that are highly tailored to those sectors.
DarwinAI
DarwinAI: DarwinAI is focused on visual quality inspection for manufacturers, providing an end-to-end solution to improve product quality and increase production. It does not offer the broad range of enterprise AI applications that C3 AI does.
DataRobot
DataRobot: DataRobot operates as an AI lifecycle platform with ecosystem integrations, offering solutions in augmented intelligence, data engineering, and machine learning. While it serves multiple sectors, it does not have the same level of pre-built enterprise AI applications as C3 AI.
H2O.ai
H2O.ai: H2O.ai delivers an advanced AI cloud platform that helps solve complex business problems. It is more focused on general AI and machine learning capabilities rather than the specific enterprise AI applications and feature store offered by C3 AI.
Microsoft Azure
Microsoft Azure: Microsoft Azure is a cloud computing service that allows for building, testing, deploying, and managing applications. While it provides a broad range of AI and machine learning tools, it does not offer the integrated suite of enterprise AI applications and the C3 AI Type System that C3 AI provides.
Key Differences
Integration and Interoperability
Integration and Interoperability: C3 AI’s Type System stands out for its ability to integrate programs and data structures from different programming languages and computational models, making it highly interoperable. This is a unique feature compared to many of its competitors.
Pre-built Applications
Pre-built Applications: The extensive library of turnkey enterprise AI applications offered by C3 AI is a significant differentiator. This allows organizations to quickly deploy AI solutions without the need for extensive development time.
Feature Management
Feature Management: The centralized Feature Store in C3 AI is a powerful tool for managing and reusing machine learning features, which is not a standard feature in many of its competitors.
In summary, while competitors like SparkCognition, DarwinAI, DataRobot, and H2O.ai offer strong AI and machine learning capabilities, C3 AI’s unique features such as its Feature Store, C3 AI Type System, and extensive library of turnkey enterprise AI applications set it apart in the market.
C3.ai - Frequently Asked Questions
What is the C3 AI Feature Store, and how does it benefit model development?
The C3 AI Feature Store is a central hub for storing, reusing, and sharing machine learning features. It streamlines model development by providing a feature registry where users can find, define, and incorporate features easily. This registry includes cataloging and search capabilities, which enhance experimentation, standardization, and collaboration across teams. Additionally, the feature store allows for the creation of features using over 200 pre-built functions, promotes reusability, and ensures feature lineage for model and experiment reproducibility.
How has C3 AI changed its pricing model, and what are the key features of the new model?
C3 AI has transitioned from a subscription-based model to a consumption- or usage-based pricing model. This change aligns with the prevalent cloud usage models and current economic conditions. Under the new model, customers get a six-month pilot subscription that includes one AI Enterprise application, unlimited use of the C3 AI Platform, unlimited developer and runtime licensing, and concierge technical support and training. After the pilot, the pricing is 55 cents per vCPU hour. This model is expected to result in a higher number of smaller deals and better aligns with customer expectations and experiences with major cloud providers and SaaS vendors.
What types of Enterprise AI applications does C3 AI offer?
C3 AI provides over 130 turnkey Enterprise AI applications that cater to various industries such as manufacturing, financial services, government, utilities, oil and gas, and more. These applications include ready-to-use suites like the AI CRM Suite, Asset Performance Suite, Defense & Intelligence Suite, Financial Services Suite, and Supply Chain Suite, among others. These applications are designed to meet business-critical needs and can be deployed quickly to solve high-value use cases.
What is the C3 AI Type System, and how does it facilitate application development?
The C3 AI Type System is a data object-centric abstraction layer that binds various C3 AI Platform components, including infrastructure and services. It allows programs, algorithms, and data structures written in different programming languages to interoperate without needing to understand the underlying physical data models. This system provides RESTful interfaces and programming language bindings, enabling developers and data scientists to focus on delivering immediate value without dealing with the complexities of the underlying systems. It supports multiple object inheritance and automatic processing of data changes, making it easier to develop and deploy production AI, big data, and predictive analytics applications.
How does C3 AI support the development and deployment of AI applications?
C3 AI provides an integrated family of development tools, including deep code, low code, and no code options, available in a collaborative multi-functional environment through C3 AI Studio. The platform offers a model-driven architecture that abstracts underlying platform services, allowing developers to build AI applications quickly. C3 AI also offers various engagement paths such as executive briefings, technology assessments, production trials, and deployment in production, which help in identifying high-impact business problems and rapidly building AI applications to solve them.
What kind of support and resources does C3 AI offer to its customers?
C3 AI provides several support and resource options. During the six-month pilot subscription, customers receive concierge technical support and training. Additionally, C3 AI offers executive briefings, technology assessments, and production trials to help customers understand and utilize the platform effectively. The company also provides resources such as the C3 AI Studio, which includes a range of development tools, and the C3 AI Type System, which simplifies the development and deployment of AI applications.
How does the C3 AI Feature Serving mechanism work?
The C3 AI Feature Serving mechanism allows for serving ML models with up-to-date data as needed. By separating the data pipelines from the ML models, the platform ensures that even large aggregation-based and compute-heavy features can be served to models immediately. This approach ensures that all predictions and insights are timely and relevant.
Can C3 AI applications be integrated with other cloud services?
Yes, C3 AI applications can be integrated with other cloud services. For example, the C3 Generative AI: Standard Edition is available on the AWS Marketplace, which allows for seamless integration with other AWS services. The C3 AI Type System also provides RESTful interfaces and programming language bindings, enabling interoperability with external systems and cloud infrastructure services.
What is the typical deployment timeline for C3 AI applications?
The deployment timeline for C3 AI applications can vary but generally follows a structured approach. It starts with an executive briefing, followed by a technology assessment (2-3 days), a production trial (8-12 weeks), and finally, the deployment in production (3-6 months). This process helps in identifying high-impact business problems and rapidly building and deploying AI applications to solve them.
How does C3 AI ensure feature lineage and model reproducibility?
C3 AI ensures feature lineage and model reproducibility through its feature store, which documents the relationships between features, models, and data snapshots. This end-to-end lineage enables model and experiment reproducibility at scale, which is crucial for scaling machine learning practices.