AI-Enabled Flutter App Development
Budget / Salary₹12,500–37,500
TypeFreelance project
LocationRemote
Posted1 hour ago
I’m building a cross-platform Flutter mobile app that relies on an “agentic” AI experience driven by natural-language processing. Your task is to own the full Flutter implementation and wire it up to my existing RESTful backend.
The AI layer
Users will interact with an in-app conversational assistant. You’ll call my NLP endpoint, manage streaming responses, and present them in a chat-style UI while gracefully handling latency, errors, and token limits. The architecture should keep the assistant logic modular so additional skills such as image recognition or predictive analytics can be added later without refactoring the core app.
Backend connectivity
Two API groups are already documented in OpenAPI (JSON):
• Database management endpoints that deliver and persist user-specific data
• Authentication endpoints providing sign-up, login, refresh, and role handling
You’ll integrate both, maintain secure storage of tokens, and respect the backend’s rate-limit headers. Future payment processing hooks may surface, so structuring the client for easy expansion is appreciated.
Core deliverables
1. Flutter (stable channel) project targeting Android & iOS, null-safe, following Clean Architecture or BLoC pattern.
2. Fully wired NLP assistant module with loading states, error handling, and retry logic.
3. Encapsulated data layer consuming database and auth APIs with Dio or http, plus unit tests.
4. Build-ready project, README with environment setup, and a short Loom walkthrough showcasing flows.
Acceptance criteria
• Successful authentication, data fetch, and NLP conversation on both platforms in emulator or physical device.
• Code passes flutter analyze and >80% unit-test coverage on core logic.
• No hard-coded secrets; all keys pulled from .env or native keychain/Keystore.
If you’ve shipped production Flutter apps that talk to GPT-style services, let’s move fast—I’m ready to grant repo access and start the sprint.
The AI layer
Users will interact with an in-app conversational assistant. You’ll call my NLP endpoint, manage streaming responses, and present them in a chat-style UI while gracefully handling latency, errors, and token limits. The architecture should keep the assistant logic modular so additional skills such as image recognition or predictive analytics can be added later without refactoring the core app.
Backend connectivity
Two API groups are already documented in OpenAPI (JSON):
• Database management endpoints that deliver and persist user-specific data
• Authentication endpoints providing sign-up, login, refresh, and role handling
You’ll integrate both, maintain secure storage of tokens, and respect the backend’s rate-limit headers. Future payment processing hooks may surface, so structuring the client for easy expansion is appreciated.
Core deliverables
1. Flutter (stable channel) project targeting Android & iOS, null-safe, following Clean Architecture or BLoC pattern.
2. Fully wired NLP assistant module with loading states, error handling, and retry logic.
3. Encapsulated data layer consuming database and auth APIs with Dio or http, plus unit tests.
4. Build-ready project, README with environment setup, and a short Loom walkthrough showcasing flows.
Acceptance criteria
• Successful authentication, data fetch, and NLP conversation on both platforms in emulator or physical device.
• Code passes flutter analyze and >80% unit-test coverage on core logic.
• No hard-coded secrets; all keys pulled from .env or native keychain/Keystore.
If you’ve shipped production Flutter apps that talk to GPT-style services, let’s move fast—I’m ready to grant repo access and start the sprint.
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