Sold by: Sparkflows.ai
Deployed on AWS
Free Trial
Sparkflows is an enterprise self-service Data, Analytics, and Agentic AI platform that enables business and technical users to prepare, blend, analyze, and operationalize data through visual no-code/low-code workflows. The platform brings together analytics automation, data engineering, Data Science & MLOps, Generative AI, intelligent assistants, and AI agents in one environment helping organizations automate complex workflows and move from data to insights, decisions, and actions faster.
Overview
Sparkflows - Self-Service Data Analytics, Agentic AI & Automation Platform
Sparkflows is an enterprise-grade, self-service Data Analytics, Agentic AI, and Automation platform that brings together AI Agents, Generative AI, Business Intelligence, Data Science & MLOps, and Data Engineering in a unified no-code/low-code environment.
Deployed via AMI on Amazon EC2, Sparkflows enables business users, analysts, data scientists, and engineering teams to connect, prepare, blend, analyze, and operationalize enterprise data; build AI and machine learning solutions; and automate complex business workflows without extensive coding. With 450+ pre-built processors, 50+ ready-to-use AI agents, and pre-built templates, teams can accelerate development and move from data and experimentation to production faster.
AI Agents & Intelligent Automation
- Build enterprise AI agents using a visual Agent Builder and drag-and-drop workflows
- Create multi-step and multi-agent workflows combining LLMs, RAG, enterprise data, ML models, APIs, and business logic
- Build Generative AI applications and intelligent assistants using structured and unstructured enterprise data
- Accelerate development with pre-built AI agents and reusable agent templates
- Automate complex business processes with human-in-the-loop controls
Self-Service Data Analytics & Business Intelligence
- Connect, prepare, cleanse, blend, and analyze data from multiple enterprise sources
- Enable self-service analytics for business users and analysts through visual no-code/low-code workflows
- Build dashboards, KPIs, reports, visualizations, and analytical applications
- Automate repeatable analytics and reporting workflows to reduce manual data preparation
- Turn enterprise data into actionable insights for faster decision-making
Data Science, Machine Learning & MLOps
- Build classification, regression, clustering, NLP, forecasting, and predictive analytics models
- Work with H2O, Scikit-learn, SparkML, XGBoost, and other machine learning frameworks
- Develop, experiment with, deploy, monitor, and operationalize ML models with MLOps capabilities
- Embed machine learning models directly into analytics, applications, and AI agent workflows
Data Engineering & Workflow Automation
- Build and automate ETL and ELT data pipelines using visual workflows
- Prepare, transform, validate, and process structured and unstructured data
- Orchestrate scalable data pipelines across cloud and enterprise environments
- Support data quality, scheduling, lineage, governance, and reusable data workflows
Built for AWS
Sparkflows integrates across the AWS data, analytics, AI, and compute ecosystem:
- Amazon EC2: Deploy and run Sparkflows workloads
- Amazon S3: Access and process enterprise data and data lakes
- Amazon EMR & AWS Glue: Scale data engineering and processing
- Amazon Redshift: Connect analytics and data warehouse workflows
- Amazon Kinesis: Process streaming and real-time data
- Amazon SageMaker: Build and deploy machine learning solutions
- Amazon Bedrock: Use foundation models for Generative AI, RAG, intelligent assistants, and AI agents
Sparkflows provides a unified visual environment for self-service analytics, data engineering, machine learning, Generative AI, Agentic AI, and intelligent automation, helping organizations move faster from data to insights, AI, decisions, and automated actions.
Highlights
- Unlock more value from your AWS data with Sparkflows. Combine Data Analytics, BI, AI Agents, Generative AI, and Data Science in a self-service, low-code/no-code platform. Build agents, automate workflows, create dashboards, and develop AI/ML applications faster. Sparkflows integrates with Amazon Bedrock, SageMaker, EMR, S3, Redshift, Glue, and Kinesis, helping teams turn enterprise data into insights, intelligent automation, and production-ready AI all from one unified platform.
- Connect enterprise data through Amazon S3, Redshift, and Kinesis. Run workloads on EC2, EMR, and AWS Glue. Build and deploy ML models with SageMaker and power GenAI and AI agents with Amazon Bedrock all from a unified platform.
- Deploy governed AI and analytics with role-based access, audit trails, monitoring, and enterprise security. SOC 2, ISO/IEC 27001:2022, and HIPAA certifications support enterprise requirements, with 90+ industry accelerators across BFSI, Healthcare, CPG, Manufacturing, and more.
Details
Sold by
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
AmazonLinux Amazon Linux 2023
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free for 21 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
m4.xlarge Recommended | $0.45 |
r5.12xlarge | $0.55 |
r5.metal | $0.55 |
r5.8xlarge | $0.55 |
m3.xlarge | $0.35 |
m4.10xlarge | $0.65 |
m4.16xlarge | $0.65 |
r5.24xlarge | $0.55 |
m4.2xlarge | $0.65 |
r5.4xlarge | $0.45 |
Dimensions summary
You pay by the hour based on the AWS instance size you run the platform on. Pricing scales with compute capacity, so larger instances cost more per hour. The r5 family offers memory-optimized options across many sizes, from r5.xlarge up to r5.24xlarge and r5.metal. The m3 and m4 families provide general-purpose compute across sizes like m4.large through m4.16xlarge. The t2.2xlarge and t3.2xlarge add burstable options. You choose the instance that fits your workload and pay only for the hours you use.
Top-of-mind questions for buyers
You pay per hour that the instance runs. The rate matches the instance size you pick, such as r5.xlarge or m4.16xlarge. Larger instances carry more memory or compute and cost more per hour. You pay the software hourly charge plus the underlying AWS compute fee.
The hourly software charge meters running time only. A fully stopped instance does not accrue software charges. You may still pay AWS for attached storage while the instance is stopped. To avoid software charges, stop the instance when not in use.
The r5 family gives more memory per instance, which suits memory-heavy data and AI workloads. The m3 and m4 families balance memory and compute for general-purpose use. Each size meters the same way, per running hour. You choose the family and size that fit your workload and pay that rate.
docs.sparkflows.ai
Helpful?
Vendor refund policy
Please contact us at support@sparkflows.io if there is need for refund.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
The latest Sparkflows release (up to version 3.3.30) brings significant improvements across AI, security, workflow orchestration, and integrations.
Key highlights include:
- AI & Copilot: AI & Copilot: Natural language querying, chatbot export/import, and enhanced Copilot capabilities
- Feedback button for AI responses
- Admin visibility into feedback and reported issues
- Email notifications for issue reporting
- AI-generated content disclaimer
- Security: Dedicated CORS Configuration Page : A new CORS Settings page has been implemented for managing cross-origin configurations centrally.
- Workflow Enhancements: Dynamic EMR scaling, MWAA SSL control, SFTP & Email nodes
- Data & Integrations: Support for Confluence, ServiceNow, SharePoint, and Pinecone
- Databricks Expansion: Advanced operators for clusters, jobs, and notebooks
- Pipeline Orchestration: Workflow-to-workflow parameter passing using ${NAME}
Additional details
Usage instructions
Sparkflows is running on port "8080 for http & 8443 for https" when instance is launched. Access it in your browser by going to:
- http://INSTANCE_PUBLIC_ADDRESS:8080
- https://INSTANCE_PUBLIC_ADDRESS:8443
- For HTTPS URL to work, Port HTTPS(443) & 8443 Should be open Login with below to get started:
- Username : admin
- Password : instance id of your machine Administrative (command-line) access can be obtained through ssh ec2-user@INSTANCE_PUBLIC_ADDRESS. Sparkflows runs under linux user account "ec2-user". For additional information, or any issue, please see our docs at https://docs.sparkflows.io/en/latest/user-guide/index.html For Compute Connection Integration, please see our docs at https://docs.sparkflows.io/en/latest/user-guide/connection/compute-connection/index.html
Support
Vendor support
Sparkflows offers multiple support channels to help customers get up and running quickly and resolve issues at any stage:
Documentation: Full installation, administration, and user guides at docs.sparkflows.ai Video Tutorials: Step-by-step walkthroughs at sparkflows.ai/videos Community Forum: Peer and expert support at community.sparkflows.ai Direct Support: Raise issues and contact the Sparkflows team at sparkflows.ai/contact-us Professional Services: Available for onboarding, implementation, and custom AI solution development
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
Omni is the AI analytics and embedded AI platform that combines governed metrics, Excel spreadsheets, and advanced customer-facing self-service experiences, built on AWS.
Get insights 10x faster from your modern data stack.
Spoggle is an AI enabled end-to-end self-service analytics platform that brings together all the analytics capabilities on a single pane of glass.
The Tableau+ Bundle offers the best flexible, AI-powered analytics with access to Tableau Cloud and Tableau Next.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.