Design & Build

Enterprise System

Anything

Your Ideas

AUTOSAD In a Nutshell

Design & Build

Enterprise Systems

SaaS Applications

Any Idea to App

Enterprise Systems

Design. Govern. Build. In Natural Language.
Create Enterprise-Grade Applications with Full SDLC Control or Prompt Your Way Through Natural Language
Empowering architecture, engineering, and governance teams with rapid execution and full traceability

What is AUTOSAD?

AUTOSAD is an AI-powered platform that turns user requirements into complete system designs, automating a large portion of the software architecture and design lifecycle - requirements engineering, system models and diagrams: which includes use-case models, use-case specifications, Interaction diagrams, application architecture and components, database design (conceptual/logical data models), deployment diagrams for on-prem as well cloud (AWS/GCP/AZURE) and API specs. It generates a comprehensive Software Architecture Document (SAD) with multi-template export.

You can natural language prompt to make or modify system architectural models. You can ask the system to generate designs for Microservices, Monolith, or Pub/Sub architecture. It includes collaboration and governance workflows so teams can go from intent to architecture in hours instead of months.

Unlike other AI code generators that create generic code. AUTOSAD follows structured Software Development Lifecycle (SDLC) methodology to generate code for your system requirements.
01

Requirements Engineering

Generate functional and non-functional requirements with natural language prompts or upload BRD/meeting transcription.

‍AUTOSAD updates downstream system models automatically when requirements change. Teams can go from intent to architecture in hours instead of months.
02

System Models

Generate use case models, interaction (sequence/communication) diagrams, data model (conceptual /logical /physical), application (component models), and deployment models directly from user requirements. Edit diagrams via built-in editors (Draw IO, Excalidraw) and export in standard formats.

Integrating with the existing system is a unique feature of AUTOSAD.
03

DIAGRAMS GPT

A single prompt adapts to the canvas you’re on (e.g., “login” becomes a requirement in the requirements view, a use case in the use case view, etc.), reducing prompt friction and cognitive load. Modify system diagrams by chatting in natural language to the diagrams.
04
Productivity and Efficiency Boost

MULTI-CLOUD DEPLOYMENTS

Generate an on-premises or cloud-specific deployment model (AWS, Azure, and GCP) from requirements.You can prompt in natural language to generate complex cloud architectures.
05

Architectural Style

Designing microservices for a complex system is hard, as its difficult to manually delineate service boundaries, decide atomic data requirements, and maintain cross-entity ACID transactions.  

AUTOSAD toggles between Microservice/Monolyth/Pub-sub architecture with just click of a button.
06

COLLABORATION


Project management, multi project support, team collaboration, versioning / history, role-based access, and share / export controls simplify multi stakeholder work.
07

UI/UX Wireframes

Generate UI/UX wireframes and screen flows directly from use case specifications and functional requirements. AUTOSAD automatically produces screen layouts, navigation flows, and component annotations — giving your team a complete visual specification from requirements through to interface design without manual handoff.

Wireframes stay in sync with requirements. When a requirement changes, the affected screen flows update automatically. Teams can export wireframes as part of the Software Architecture Document (SAD) or edit them directly using the built-in editor.
08
Productivity and Efficiency Boost

AUTOSAD Code

It takes your comprehensive system architecture and generates enterprise-grade applications that developers can actually maintain and extend. AUTOSAD transforms comprehensive system architecture and design documents into enterprise-grade applications that are deployed with click of a button, are scalable and easy to maintain.

AUTOSAD  follows structured SDLC phases, to ensure best practices in system design, reducing complexity and enabling your IT teams to efficiently manage and update the software. This approach reduces maintenance efforts, enhances agility, delivering sustainable solutions that support ongoing growth and innovation.
01

Requirements Engineering

RE covers how teams elicit, analyze, specify, validate, and manage functional and non‑functional requirements so that systems meet stakeholder needs. Typical pain points include ambiguity, incomplete coverage, inconsistent updates across downstream artifacts, and the rework caused by requirement changes.
02

Use Case Models

Use-case models capture how external actors (users, systems) achieve goals with a system, defining scope and functional behavior at a black box level. Use-case models give you a clean, stakeholder‑friendly map of system behavior; AUTOSAD layers GenAI on top to derive those models directly from requirements, keep them consistent as things change, and push them forward into concrete design and implementation artifacts (APIs, data, deployments). This shortens the path from “what users need” to “what we automate.”
03

Interaction Diagram

Show the message-by-message collaboration among actors and system parts to realize a use case path. Common forms: Sequence diagrams (lifelines, messages, alt/opt fragments), Communication diagrams (links and message numbering). Why it matters: clarifies responsibilities, timing, error paths, and interfaces derived from the use case steps.
04

System Conceptual Design

Capture the system’s intent, scope, external actors/systems, major information flows, and key quality attributes (NFRs) before any detailed design or code. Typical outputs include a system context diagram (often following the C4 model’s “System” level), an initial set of use cases, and early decisions about architectural style and boundaries.
05
Productivity and Efficiency Boost

Physical Data Models

A high-level view of the domain (key entities and relationships) in business terms, independent of technology. Logical data model: a more detailed, normalized structure with attributes, keys, and cardinalities, still technology‑agnostic. Physical data model: the implementation-ready data design tailored to a target platform (naming, datatypes, storage, and other physical considerations).
06

Interface Diagrams

There are two approaches for API design, bottom-up and top-down. Traditional software development uses bottom-up, APIs are exposed once the system is built, but this approach does not yield good results. AUTOSAD uses top-down to represent business intent in the AIPs. From requirements, use cases, and data models, AUTOSAD proposes API endpoints and produces swagger definitions.

On-Prem & Cloud Deployments

AUTOSAD turns conceptual system design plus your requirements (including NFRs) into concrete, provider‑specific deployment models for on‑prem and the major clouds, editable via natural language, kept consistent across all diagrams, and packaged into a living architecture document. This shortens design cycles and improves traceability from requirements to deployment.

If you create short description of your system and key NFRs, the AUTOSAD deployment agent will generate onprem/AWS/GCP/Azure deployment models.

Develop Enterprise Grade Systems ( AWS/GCP/AZURE)
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Design Canvas

Our intelligent AI recommends the architecture of your system based on requirements. You can select from the following.

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Monolith Application Architecture

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Micro-Services based Architecture

Governance Without Compromise

AUTOSAD enforces architecture governance at every layer — capability, control, and strategy — before a single line of code ships. Run on-premises or in your own cloud to keep requirements, models, and prompts within your jurisdiction, with full traceability from requirement to deployment.

Govern Enterprise-Grade Systems

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Functional Requirements

Functional requirements define what the system should do. They outline specific features, behaviors, and interactions expected from AUTOSAD.

1. Clarity: Ensure requirements are clear and understandable.
2. Consistency: Avoid conflicts and redundancies.
3. Stakeholder Involvement: Engage users and stakeholders early and continuously.
4. Prioritization: Rank requirements by importance and feasibility.
5. Traceability: Maintain links between requirements and their origins.
6. Flexibility: Be open to changes and updates.
economically viable.
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Non-Functional Requirements

Non-functional requirements address system qualities like performance, security, and usability. AUTOSAD ensures a robust and reliable experience.

1. Clarity: Define non-functional requirements clearly and precisely.
2. Measurability: Ensure they can be measured or quantified.
3. Realism: Set achievable and realistic goals.
4. Prioritization: Determine which non-functional requirements are most critical.
5. Consistency: Maintain consistency with functional requirements and each other.
6. Documentation: Keep well-organized records of non-functional requirements.
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Use Case Models

Use case models depict system interactions from a user’s perspective. Autosad covers scenarios like model creation, parameter tuning, and result analysis.

1. Clarity: Ensure use cases are understandable and unambiguous.
2. Completeness: Cover all scenarios, including alternate and exception paths.
3. Consistency: Align use cases with functional requirements and each other.
4. Stakeholder Involvement: Engage users and stakeholders to validate use cases.
5. Documentation: Maintain detailed and organized records of use cases.
6. Prioritization: Identify and focus on the most critical use cases first.
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Interaction Diagrams

Interaction models illustrate how different system components communicate. Autosad’s interaction models ensure seamless coordination between AI algorithms and user inputs.

1. Clarity: Make diagrams easy to read and understand.
2. Completeness: Include all relevant interactions and messages.
3. Consistency: Ensure diagrams are consistent with use cases and requirements.
4. Stakeholder Involvement: Get feedback from stakeholders to validate interactions.
5. Documentation: Keep well-organized records of all interaction diagrams.
6. Prioritization: Focus on key interactions that are critical to the system.
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Data Models

Data models are abstract representations that define the structure, organization, and relationships among data elements in a system.

1. Clarity: Ensure data models are easy to understand and interpret.
2. Completeness: Include all necessary entities, attributes, and relationships.
3. Consistency: Align data models with business requirements and other system models.
4. Stakeholder Involvement: Engage stakeholders to validate the accuracy and relevance of the data model.
5. Documentation: Keep detailed and organized records of data models.
6. Normalization: Ensure data is structured efficiently to avoid redundancy.
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Application Models

Application models are abstract representations that define the structure, behavior, and interactions of the various components of an application.

1. Clarity: Ensure component models are easy to understand with clear interfaces and responsibilities.
2. Completeness: Include all necessary components and their interactions.
3. Consistency: Maintain alignment with architectural principles and other system models.
4. Stakeholder Involvement: Engage stakeholders, including developers, to validate component models.
5. Documentation: Keep well-documented records of all components and their relationships.
6. Reusability: Design components to be reusable across different parts of the application.
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Deployment Models

Deployment models define how Autosad goes live. Whether on-premises or in the cloud, Autosad ensures smooth deployment and scalability.

1. Clarity: Ensure deployment models are easy to understand, showing system components and their deployment locations.
2. Completeness: Include all necessary nodes, hardware, and network configurations.
3. Consistency: Align deployment models with architectural and application requirements.
4. Stakeholder Involvement: Engage stakeholders, including IT and operations staff, to validate deployment plans.
5. Documentation: Maintain detailed and organized records of the deployment model.
6. Scalability: Design the model to accommodate future growth and increased load.
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