Python Script - Intercom API
LANCER
Lancer :
Ideal for quick, focused engagements
Team: ≤ 2 resources
Duration: ≤ 3 weeks
Indicative Budget: ≤ $3,000 USD*
Use Cases: MVPs, prototypes, simple websites, bug-fix sprints
Indicative Pricing: ~$15–$25/hr per resource*
Growth :
Best suited for growing products or structured builds
Team: 2–5 resources
Duration: Up to 4 months
Indicative Budget: Up to $30,000 USD*
Use Cases: Feature-rich web apps, integrations, custom dashboards
Indicative Pricing: ~$15–$35/hr per resource*
Enterprise :
Tailored for high-scale, complex or long-term initiatives
Team: 5+ resources
Duration: More than 4 months
Indicative Budget: Starts from $30,000+ USD*
Use Cases: End-to-end platforms, SaaS products, compliance-heavy systems
Indicative Pricing: ~$25–$50/hr depending on roles*
(Development)
Project Description
Aqua Networks Limited engaged Oodles to finalize and deploy a Python script that bridges conversations between Intercom and Telegram. The goal was to enable real-time communication where customer messages sent via Intercom would be routed to a Telegram bot for immediate response and engagement.
Scope Of Work
The client required Oodles to validate and complete a pre-written Python script that integrates the Intercom API with a Telegram bot. The main tasks included reviewing and testing the existing code, launching the bot within a Dockerized environment, and ensuring smooth communication flow between the platforms. The engagement also included provision for resolving additional Python issues in subsequent project phases.
Our Solution
To successfully launch the integration and prepare it for long-term use, Oodles delivered:
- Reviewed and validated the existing Python codebase for functionality and structure
- Dockerized the script to ensure containerized, environment-independent deployment
- Configured and deployed the solution on the client’s preferred infrastructure (DigitalOcean)
- Enabled seamless message relay from Intercom to Telegram via the bot
- Added basic logging and error-handling mechanisms for debugging and uptime monitoring
- Provided handoff documentation for launching and maintaining the bot
- Initiated support for future enhancements and Python-based automation tasks
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