Sold by: Sparkflows.ai
Deployed on AWS
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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
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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 EC2 instance type you run Sparkflows on. Billing is usage-based, so charges scale with how many hours each instance runs. The options span three instance families: the t2 and t3 general-purpose burstable types, the m3 and m4 general-purpose types, and the r5 memory-optimized types. Within each family, larger sizes carry more compute and memory capacity, so you select the size that fits your workload. There are no fixed tiers or commitments; your cost tracks the running hours of your chosen instance.
Top-of-mind questions for buyers
One unit is one hour that a single AWS EC2 instance of the chosen type runs Sparkflows. If you run two instances, each accrues its own hourly charge. Your bill reflects total running hours across all instances you launch.
The hourly software charge applies only while the instance runs. Stopped or paused instances do not accrue Sparkflows hourly fees. Note that underlying AWS storage for a stopped instance may still incur separate AWS charges billed by AWS, not by Sparkflows.
The t2, t3, m3, and m4 general-purpose families balance compute and memory. The r5 memory-optimized family provides more memory relative to compute. You pick a family based on whether your data preparation, analytics, or model workloads need more processing power or more memory.
docs.sparkflows.ai
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Vendor refund policy
Please contact us at support@sparkflows.io if there is need for refund.
Legal
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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.
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