Picky Assist
AI Powered Chatbots, WhatsApp Business API, Social CRM, Machine Learning, Natural Language Processing, Phone Automation
Integrate the Picky Assist API with the Go API
Setup the Picky Assist API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Picky Assist and Go remarkably fast. Free for developers.
Popular Picky Assist and Go Actions#
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Overview of Picky Assist#
Picky Assist bridges your communication channels with smart automation, letting you weave SMS, WhatsApp, and other messaging services into your business workflows. By integrating with Pipedream, you can automate interactions with customers, streamline notifications, or orchestrate multi-platform messaging campaigns. The API enables you to trigger messages based on events, sync conversations to CRMs, or even dispatch alerts from monitoring systems.
Connect Picky Assist#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
picky_assist: {
type: "app",
app: "picky_assist",
}
},
async run({steps, $}) {
const data = {
"token": `${this.picky_assist.$auth.api_token}`,
}
return await axios($, {
method: "post",
url: `https://pickyassist.com/app/api/v2/check-balance`,
data,
})
},
})
Overview of Go#
You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.
Connect Go#
package main
import (
"fmt"
pd "github.com/PipedreamHQ/pipedream-go"
)
func main() {
// Access previous step data using pd.Steps
fmt.Println(pd.Steps)
// Export data using pd.Export
data := make(map[string]interface{})
data["name"] = "Luke"
pd.Export("data", data)
}