To extract data from Reply.io, you need to access its API. First, log in to your Reply.io account and navigate to the API settings. Generate an API key if you don't have one already. This key will authenticate and authorize your requests to the Reply.io API.

Determine which data you need to move to Redis, such as contact lists, email sequences, or campaign results. Consult the Reply.io API documentation to understand the available endpoints and the structure of the data you wish to extract.

Create a script using a programming language like Python to call the Reply.io API. Use the requests library to make HTTP GET requests to the desired endpoints. Ensure you include the API key in the request header for authentication. For example:
```python
import requests

api_key = 'your_reply_io_api_key'
headers = {'Authorization': f'Bearer {api_key}'}
response = requests.get('https://api.reply.io/v1/your_endpoint', headers=headers)
data = response.json()
```

Once you receive the data from the API, parse the JSON response to extract the necessary information. Organize the data into a format suitable for storage in Redis, such as key-value pairs or hashes, depending on your data structure requirements.

Install and set up Redis on your desired server or local machine if it's not already available. You can download Redis from its official website and follow the installation instructions for your operating system. Start the Redis server to begin accepting connections.

Extend your existing script to include functionality for connecting to Redis and inserting the structured data. Use a Redis client library like redis-py in Python to establish a connection and perform data operations. For example:
```python
import redis

r = redis.StrictRedis(host='localhost', port=6379, db=0)
# Assuming data is a dictionary
for key, value in data.items():
r.set(key, value)
```

To ensure the data in Redis is up-to-date, automate the script execution using a scheduler like cron on Linux or Task Scheduler on Windows. Set it to run at regular intervals, such as daily or weekly, depending on how frequently the data changes.

By following these steps, you can effectively move data from Reply.io to Redis using custom scripts without relying on third-party connectors or integrations.