Sold by: Inadev
Deployed on AWS
4X the Speed | 1/3 the Cost
Ceebit is an agentic AI platform that integrates cross-functional teams, tools, and workflows into a unified development ecosystem at 4X the speed and 1/3 the cost. By orchestrating product, engineering, platform, and DevSecOps tools with full AI governance, Ceebit automates critical steps in the software lifecycle, from user story generation and code development to testing, deployment, impact analysis and operations and maintenance. The result: faster delivery, lower cost, and greater mission impact. This is why Ceebit is trusted by Federal Agencies and Fortune 500 companies.
Overview
Ceebit is an agentic AI platform designed to accelerate enterprise application development on AWS. Rather than simply using AI as an assistant, Ceebit orchestrates intelligent agents that coordinate tasks across development, integration, and operations workflows. The platform dynamically routes work to the most appropriate approach (large language models, machine learning systems, or advanced algorithms) while automatically generating the integration code required to connect services, APIs, and enterprise data sources. This reduces development friction and helps teams move from concept to production faster.
With a configure-not-code approach, Ceebit provides a visual workflow engine and automated code generation capabilities that enable teams to build and evolve web applications with minimal manual coding. Organizations can standardize development patterns, automate repetitive tasks, and deliver applications more consistently across projects.
Ceebit also includes an operational intelligence layer that continuously monitors application and infrastructure health. The system detects risks early and can proactively resolve common issues through self-healing behaviors such as dependency updates and performance bottleneck remediation.
The platform is LLM-agnostic, allowing organizations to switch between large language models based on performance, cost, or governance requirements. This flexibility future-proofs AI adoption while keeping the development and operations experience unified across the enterprise.
Highlights
- Agentic AI orchestration that intelligently routes tasks to the optimal compute method (LLMs, machine learning, or algorithms) while automatically generating the integration code required to connect enterprise systems.
- Configure-not-code development with visual workflows and automated code generation that enables teams to build and evolve web and enterprise applications with significantly less manual coding.
- Self-healing operations that continuously monitor application and infrastructure health, proactively detecting risks and resolving common issues before they impact users.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
AmazonLinux AL2023
Deployed on AWS
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Features and programs
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Deployment | One full deployment of Ceebit in the customer's AWS environment, including all infrastructure provisioning and software installation. | $20,000.00 |
Dimensions summary
Pricing uses a single dimension billed per deployment unit. You pay for one full installation of Ceebit inside your own AWS environment. This covers all infrastructure provisioning and software setup for that deployment. There are no tiers, instance sizes, or usage add-ons to choose between. The cost scales by the number of deployments you provision. Each deployment brings the platform's agentic AI capabilities for building enterprise applications. Because the platform works with any language model, your model choices do not change how this deployment charge is structured.
Top-of-mind questions for buyers
One deployment unit is a single full installation of Ceebit inside your own AWS environment. It covers all infrastructure provisioning and software setup for that installation. Each separate installation you provision counts as its own unit. You add units by provisioning additional deployments.
No. The deployment charge is fixed per installation. Ceebit works with any language model and can switch between them based on scope, cost, and suitability. Those model choices affect how the platform runs, not how the deployment charge is structured. Any language model usage costs are handled outside this deployment charge.
A deployment charge covers infrastructure provisioning and software installation for one full setup in your AWS environment. This brings the platform's agentic AI capabilities for building enterprise applications. There are no separate instance sizes, usage add-ons, or tiers to select. For scope details beyond this, contact the vendor.
www.inadev.com
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Vendor refund policy
Refunds for software charges may be requested within 7 days of purchase if the product did not perform as described or a technical issue prevented normal usage.
Refunds are not issued after 7 days, for misconfiguration, or change of mind.
To request a refund, email support@inadev.com with your AWS Account ID, product name, purchase date, and issue description. This policy covers software charges only. INADEV reserves the right to update this policy at any time.
Legal
Vendor terms and conditions
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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
CEEBIT-Installer Release Notes
Version 2.4.1
Overview
This release advances the CEEBOT platform through a series of strategic enhancements focused on platform consolidation, delivery intelligence, architecture governance, and scalable automation. Together, these improvements strengthen traceability, increase operational consistency, and establish a common AI operating foundation that accelerates future innovation across delivery, architecture, and engineering workflows.
Key Enhancements
Accelerating Platform Consolidation & Governance
Strengthening platform consistency through a unified operating model and modernized architecture.
- Foundation & Estate Rationalization initiatives to streamline platform operations and establish a single governance framework across the CEEBOT ecosystem.
- Modernized core story generation, synchronization, and document intelligence capabilities, improving alignment between planning, delivery, and knowledge assets.
Why this matters: A consolidated governance model reduces operational complexity, improves consistency across teams, and creates a stronger foundation for enterprise-scale adoption.
Establishing a Unified AI Operating Platform
Advancing a shared services architecture that enables scalable innovation across current and future CEEBOT personas.
- Delivered the Shared CEEBOT Engine, providing a centralized intelligence layer that supports Story Grooming, Delivery, Architecture, and future AI capabilities.
- Standardized core platform services to simplify ongoing enhancements and enable faster propagation of improvements across all CEEBOT experiences.
- Created a scalable platform foundation designed to support continued expansion without duplicating capability development.
Why this matters: A shared AI operating platform improves scalability, reduces maintenance overhead, and accelerates the delivery of new capabilities across the enterprise ecosystem.
Strengthening Delivery Intelligence & Traceability
Expanding delivery knowledge services to improve contextual understanding, delivery insights, and automation readiness.
- Delivered and integrated the Knowledge Graph with the Story Grooming workflow, enhancing contextual traceability across requirements and delivery artifacts.
- Established foundational Code Intelligence capabilities, including enterprise-grade code search and repository interaction services for GitHub-based assets.
- Laid the groundwork for future integration between delivery knowledge services and code generation workflows.
Why this matters: Enhanced traceability and knowledge connectivity enable more informed decision-making, increase delivery confidence, and support higher levels of automation across the software lifecycle.
Enhancing Intelligent Delivery Orchestration
Continuing to mature delivery planning and execution workflows through improved automation and scalability.
- Advanced feature-grouping intelligence within the Delivery Agent to improve workstream organization and planning outcomes.
- Refined orchestration capabilities that better align delivery activities with implementation objectives.
Why this matters: Improved delivery orchestration helps organizations manage increasing solution complexity while maintaining planning accuracy and execution efficiency.
Advancing Architecture Governance & Collaboration
Improving architectural visibility and establishing stronger design management practices.
- Architecture Workspace, providing a centralized environment for architecture management and governance activities.
- Introduced foundational capabilities that support architecture review, collaboration, and decision tracking across delivery initiatives.
Why this matters: Centralized architectural governance improves consistency, promotes enterprise standards, and strengthens alignment between solution design and delivery execution.
Scaling Delivery-to-Code Automation
Furthering the vision of end-to-end implementation orchestration through a unified code generation baseline.
- Automated the flow from Delivery Agent outputs into implementation planning workflows.
- Enhanced workflow traceability by capturing implementation plans within workflow history and change tracking processes.
- Established implementation initiation workflows and integrated code execution services into the automation pipeline.
- Continued progress toward a unified code generation framework capable of transforming implementation plans into executable development outcomes.
Why this matters: Greater alignment between planning, implementation, and execution reduces manual coordination effort, improves transparency, and supports accelerated delivery cycles.
Release Summary
This release marks a significant step forward in the evolution of the CEEBOT platform, delivering a unified AI foundation, strengthened delivery intelligence, enhanced governance capabilities, and expanded automation readiness. These investments position the platform for greater scalability, improved traceability, and accelerated enterprise delivery outcomes.
Version 2.4.0
Highlights
This release introduces a dedicated Testgenie artifact pipeline, Grafana air-gapped support with a custom image, an expanded JIRA / Entra (Azure AD) integration surface in the platform layer, hardened Bedrock IRSA permissions, and private RDS Data API access via a new VPC endpoint. It also bundles stability fixes for Grafana unified search and SonarQube startup in restricted networks.
Key Changes
Security and Compliance
- Hardened Bedrock IRSA Secrets Manager permissions to cover the full secret lifecycle.
- Extended events:PutEvents targets on the Bedrock role to include the un-suffixed event-bus/prism-events.
- Added scoped s3:Get* / s3:Put* / s3:List* permissions on the new Testgenie artifact bucket to the Bedrock IRSA role.
- Testgenie S3 bucket provisioned with aws:kms encryption, versioning, full public-access block, and non-current version lifecycle expiration.
Infrastructure and Platform
- Added a new S3 bucket for Testgenie code artifacts.
- Added a private RDS Data API Interface VPC endpoint (com.amazonaws.<region>.rds-data).
- Expanded JIRA / Entra integration surface.
- Added optional GITHUB_API_BASE_URL for GitHub Enterprise Server support.
Observability and Tooling
- New Grafana copies dashboards from a baked-in image path instead of downloading them.
- SonarQube copies bundled plugins from the image into the extensions PVC.
UI and Documentation
- Added JIRA variables in the UI
- Added GitHub API Url in the UI
Summary
Major work concentrated in irsa role, rds vpc Endpoint, testgenie s3 bucket feature and airgapped grafana and sonarqube installation
Additional details
Usage instructions
Follow the steps below to configure and operate the solution after launching the AMI:
- Access the Application
Open your web browser and navigate to: http://<server-public-ip>:5000
Ensure that the instance security group allows inbound access to port 5000 from your network.
- Review Prerequisites
Before proceeding, go to the Document tab within the application UI and review all prerequisites carefully.
- Configuration (Tabs 1 and 2)
Provide the necessary configuration details:
AWS Settings: AWS Access Credentials Domain Name DNS Provider Configuration SSL Certificate ARN License: Enter valid CEEBIT license key(s) Enter valid CEEBIT CodeCommit license key(s) Advanced Settings (Advanced Tab): SMTP configuration (for notifications) JIRA integration (for issue tracking) GitHub integration (for repository access and workflows) Optional: KMS key arn (to use existing KMS key) ECR lifecycle policy (to use custom ECR lifecycle policy)
After entering all required details, click Save to persist the configuration.
- Deployment (Tab 3)
Initiate and manage infrastructure deployment:
Select the desired Action: Setup - Deploy infrastructure Teardown - Remove deployed resources Status - Check current deployment status Choose Layers: Deploy All layers (0-4) (default) or select specific layers as needed Optional: Enable "Update existing stacks" if you are redeploying or modifying existing CloudFormation stacks Click Start to begin the operation
- Monitoring (Tab 4)
Track deployment progress and logs:
View real-time logs streamed via Server-Sent Events (SSE) Download logs for audit or troubleshooting Clear logs from the interface when required
Notes Ensure IAM permissions are correctly configured before deployment Avoid modifying resources manually outside the tool to prevent configuration drift For troubleshooting, refer to logs and the Document tab guidelines
Support
Vendor support
Email: support@inadev.com What to expect: Assistance with onboarding, configuration guidance, troubleshooting, and best practices for building and operating applications with Ceebit. Response times and coverage depend on the purchased support tier and agreed support plan.
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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