AI Test Case & Code Generation
Generate web, API, and mobile test suites directly from user stories and application discovery
FranklyTest.ai
FranklyTest.ai in private beta
Prelaunch access
Frankly, your tests should write themselves.
Development moves faster than testing: FranklyTest.ai keeps the pace.
FranklyTest.ai is under construction; we’re building an AI platform that generates, runs, and self-heals automated API, web, and mobile app tests from your requirements. Python is the scripting language, and we’re leveraging different libraries to target each surface. Public access isn’t available yet.
From user stories to coverage
We’re training the system to generate deterministic tests and keep them green across API, web, and mobile flows.
Python-first automation
Early access will focus on Python scripts powered by specialized libraries for each target environment.
Problem statement
Frankly, test automation today is broken.
Software development moves faster than testing can keep up. Traditional automation pipelines are slow to author, hard to maintain, and costly to evolve. Teams spend more time fixing tests than shipping features, while coverage stalls as products accelerate.
The result is a QA stack that cannot scale with modern release velocity and cross-platform complexity.
Why it breaks down
- Slow authoring cycles make test suites lag behind product changes.
- Flaky environments and frequent UI changes force constant rework.
- Maintenance costs rise faster than coverage, slowing teams down.
- Scaling across web, mobile, and APIs becomes a coordination nightmare.
Frankly, in development
FranklyTest.ai is building the orchestration framework that turns requirements into resilient automated testing.
The flow on the right is the core platform model: it shows how requirements are ingested, how agents coordinate generation and execution, and how results are interpreted before feedback is stored for continuous learning. This framework is under construction with planned coverage across API, web, and mobile app tests, powered by Python and modern testing libraries.
- Framework-first: the orchestration map remains the source of truth for how the platform coordinates test generation and execution.
- Reliability by design: self-healing is modeled as a dedicated branch inside the framework, not a one-off script.
- Developer-first: the flow incorporates CI/CD, and can be integrated in your build pipelines.
Framework flow
Agent orchestration map
Trigger
Load User Story
Test Manager Agent
Orchestrates
Central coordination node
Framework outputs
Directed downstream flow
Application Discovery
Test Case Generation
Test Code Generation
Memory Lookup
Read-only retrieval for any step
Supports the pipeline
Merge to Run Tests
Run Tests
Test Results
Interpretation branch
Diagnostics & recovery
Analyze failures
Self-healing fixes broken tests
Analysis interprets results and explains why assertions failed. Self-healing adapts test code and then re-runs affected tests to confirm recovery.
Persist Results and Fixes
Store Memory
Write-back step that captures analysis, healing output, and execution context.
Prototype interface
Coming soon
HOW IT WORKS
FranklyTest.ai generates and heals API, web, and mobile tests in one flow.
A clear workflow that turns requirements into reliable automation across services, browsers, and native apps. The engine uses Python scripting with purpose-built libraries so suites stay current without manual upkeep.
API & UI coverage
Python automation
CI/CD ready
Workflow overview
active
Confidence output
Coverage for REST, web, and mobile surfaces with consistent Python automation you can trust.
- Versioned test artifacts for auditability.
- Auto-triage to reduce noisy failures.
- Continuous healing to keep suites stable.
Platform Features
Frankly, the fastest way to ship reliable tests.
FranklyTest.ai is built for teams that need precise coverage across web apps, APIs, and mobile experiences. Extend workflows with Python and library-based hooks when you need custom logic or specialized tooling.
Developer-ready out of the box
Self-Healing Tests
AI fixes broken selectors, flaky API assertions, and mobile flows automatically.
Multi-Target Testing
Unified coverage for browser UI, REST/GraphQL APIs, and native mobile apps.
CI/CD Integration
Runs in pipelines with artifacts for web, API, and mobile test results.
Concept preview: multi-target testing
Frankly, your requirements are enough.
Here’s a product preview of FranklyTest.ai. Drop a user story into the platform and the AI produces concrete, runnable tests. The engine selects the right libraries for each target, keeps output consistent, and summarizes any updates separately from the test code.
Example user story
As a customer, I want to add a credit card as a payment method so I can purchase items in the online web shop
- Given a signed-in account with a verified profile and no saved cards
- When a valid card is added in the web form or mobile sheet, and the API returns a payment method ID
- Then the new card appears as the default method in web and mobile, and the API lists it for billing within seconds
Concept build
Python output
Web, API, Mobile
Generated test samples
FranklyTest.ai
Generated test cases for the full user story:
- Test case 01 — Success path: Add a valid card on web, receive a payment method ID, and set it as the default method.
- Test case 02 — Invalid card details: Submit an invalid card number and confirm validation errors prevent card creation.
- Test case 03 — Expired card: Enter an expired card and verify the API rejects it and no method is saved.
- Test case 04 — Persistence: Add a valid card, refresh, and confirm the card remains listed as default across web and mobile.
- Test case 05 — Purchase after adding: Add a valid card, complete a purchase, and verify the order uses the new payment method.
Selected test code example (Test case 02)
# Generated test code by FranklyTest.ai (Python)
# Test case 02: invalid card details are rejected
import pytest
from playwright.async_api import Page
@pytest.mark.payment
async def test_invalid_card_number_shows_validation_error(page: Page, api_client):
await api_client.login_and_clear_cards()
await page.goto("https://shop.example/account/payments")
await page.get_by_role("button", name="Add card").click()
await page.get_by_label("Card number").fill("1111 2222 3333 4444")
await page.get_by_label("Expiry").fill("12/29")
await page.get_by_label("CVC").fill("123")
await page.get_by_role("button", name="Save card").click()
await page.get_by_text("Invalid card number").wait_for()
await page.get_by_text("Card saved").is_hidden()Platform note
The Add card button name changed; FranklyTest.ai updated the locator and kept the API verification intact.
Product preview only; the platform is currently in development.
Contact FranklyTest.ai
Frankly, we’re still under construction and we want your input.
FranklyTest.ai is building AI-powered test automation for API, web, and mobile apps. We generate, execute, and self-heal tests from your requirements using Python and modern libraries. If you want early access, tailored demos, or partnership conversations, reach out directly.
Prefer a quick intro? Email us directly at [email protected].
Under construction
Private beta
What we’re looking for
- Design partners for early feedback
- Teams with CI/CD pipelines to integrate
- Developers who want tests generated from stories
Start the conversation
Beta interest, demo requests, partnerships, or just technical feedback. We’re listening.
Email the teamScope
API, web, and mobile app testing with Python
Multi-library support designed for modern QA and DevOps teams.
FranklyTest.ai
Frankly, stop writing tests.
We’re still under construction: join the beta to be first in line when FranklyTest.ai launches for API, web, and mobile app tests powered by Python and modern testing libraries.