Ellogy
Ellogy · Coding
Ellogy is an AI business analyst that interviews your team, writes software requirements, designs and test cases, then generates code, so you review instead of writing documents by hand.
About Ellogy
What Is Ellogy
Ellogy is a web platform built around a simple idea: the slowest part of building software isn't the coding, it's the talking and translating that happens before anyone writes a line. The tool runs that conversation for you. It interviews stakeholders through a chatbot, turns their answers into structured requirements, and keeps going until it produces design documentation and test plans.
The appeal sits in how far that chain reaches. Most requirements tools stop at a document. Ellogy carries the work forward into UML diagrams, test scenarios, and, on higher plans, generated code and API stubs. A business analyst who normally spends weeks drafting a BRD can hand the first pass to the AI and edit from there.
The limits matter too. The output is only as good as the answers your team gives, and the AI interviews still need a human to verify scope and catch ambiguous requirements. The Basic plan caps you at roughly 30,000 words and a single seat, so larger teams either share an account awkwardly or move up to Starter.
Getting Started
- Sign up on ellogy.ai and pick a plan based on how many people need access and how much content you'll generate.
- Describe the product or feature you want, then let the AI chatbot interview you and ask follow-up questions until it understands the need.
- Review the generated user stories, use cases, and acceptance criteria, and invite teammates or outside experts to add input where the AI flags gaps.
- Generate the design documents, flow charts, and test plans from the approved requirements.
- Export everything as PDF or Word, or push the output into your development workflow, including code generation on the Starter and Enterprise plans.
Product Information
A quick look at Ellogy's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Business analysts
- Product managers
- Startup founders
- Development team leads
Tasks
- Requirement gathering
- Software design documentation
- Test planning
- Business requirements documents
- Vendor comparison
Scenarios
- Early-stage project scoping
- Enterprise digital transformation work
- Custom app delivery for clients
- AI-assisted coding projects
Key features
AI-Led Requirements Interviews
Ellogy's chatbot interviews stakeholders instead of making you fill out forms. It asks follow-up questions, confirms its understanding, and checks the request against what it already knows, so gaps surface during the conversation rather than after launch. The output is a set of user stories, scenarios, and acceptance criteria you can review.
User Stories and Acceptance Criteria
From the interview, the platform writes user stories and acceptance criteria that put a boundary around scope. That matters because scope creep rarely announces itself; it shows up as one small request at a time. Having testable acceptance criteria in writing gives you something concrete to point at when the conversation drifts.
Software Design Documentation
Ellogy groups requirements into separate use cases, then defines the roles, preconditions, and triggers for each one. From there it generates flow charts and UML-based design diagrams. The design starts from requirements instead of being drawn separately and stitched back on.
Test Plan and Test Case Generation
Each use case gets its own test plan covering objectives, scope, resources, schedule, and environment, followed by test scenarios and step-by-step cases. Teams that normally write these by hand can start from a generated draft and adjust the edges. It keeps the requirements and the tests in one traceable chain.
Code and API Generation
On the Starter plan and up, Ellogy generates code and API foundations from the requirements and designs it already produced. It connects through MCP (Model Context Protocol) to common development environments and integrates with GitHub for deployment across clouds. The point is continuity: the same requirements that shaped the design feed the code.
Bring Your Own Models and Data Controls
You pick which LLM handles which task, based on privacy, cost, or regional availability. On the Enterprise plan, Ellogy can train models on your sector knowledge, run in a dedicated cloud, and support on-premise hosting. The company states it doesn't access customer data, which matters if your requirements describe unreleased products.
Multilingual Requirements and Export
The Basic plan supports AI conversations in Arabic and English, and every plan exports to PDF or Microsoft Word. That export step is what makes the tool usable in existing workflows, since most teams still circulate documents and review them in tracked changes.
Pros and cons
Pros
- Covers the whole chain from interview to test cases, so you're not stitching together three or four separate tools.
- Generates a full BRD in a reported ~30 minutes, which cuts the first-draft work more than any single feature.
- Model choice and data hosting controls on the Enterprise plan suit teams with privacy or regional constraints.
- Exports to PDF and Word, so output slots into existing review and sign-off processes.
- Includes vendor benchmarking, useful when the build-versus-buy question is still open.
Cons
- The Basic plan allows only one seat and about 30,000 words, which gets tight for teams of any real size.
- Quality depends on the answers given during the AI interview, so vague stakeholders still produce vague requirements.
- Multilingual AI on the lower tier is limited to Arabic and English; other languages need a closer look at plan support.
- Enterprise pricing isn't published, so larger organizations have to request a quote before they can budget.
Frequently asked questions
Ellogy acts as an AI business analyst. It interviews stakeholders, writes requirements as user stories and acceptance criteria, generates design documentation and UML diagrams, produces test plans and test cases, and on higher plans generates code. You review and validate the output rather than writing it from scratch.
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