How to Build Your Own CRM with AI Voice, WhatsApp and Task Management

How to Build Your Own CRM with AI Voice, WhatsApp and Task Management

Most CRMs begin as a contact database. The useful ones become an operating system for customer conversations: every call, WhatsApp message, follow-up task and deal update appears in one place.

You do not need to start from a blank repository. Trikon’s public Voice AI Dashboard Starter already provides a Next.js and TypeScript foundation for voice agents, phone numbers, outbound calls, webhooks and call logs. You can clone the starter, retain its server-side API pattern and extend it into a CRM designed around your own workflow.

Start with the public repository: https://github.com/trikontech/voice-ai-example-dashboard

What the starter already gives you

The repository is a developer reference implementation built with Next.js, React, TypeScript and Tailwind CSS. It includes an overview dashboard, an agent embed configurator, phone-number views, an outbound-call form, call-history screens and API proxy routes.

• Voice-agent and phone-number API integrations.
• Outbound-call handling and a webhook route.
• Call logs with status, duration, outcome and detail views.
• A browser-safe public widget configuration and server-side secret-key handling.
• Clearly labelled demo data, so developers can explore the interface before connecting credentials.

The repository is a voice-first starter—not a finished CRM. Contacts, companies, deals, WhatsApp conversations, task ownership and reporting are the layers you add next. That separation is helpful because it lets you preserve the proven Voice AI connection while designing the business system around your actual sales or support process.

1. Run the starter locally

Clone the repository and install the application:

git clone https://github.com/trikontech/voice-ai-example-dashboard.git
cd voice-ai-example-dashboard
npm install
cp .env.example .env.local
npm run dev

The sample environment file supports TRIKON_API_KEY for server-side API calls, TRIKON_API_BASE_URL for the Voice AI service, NEXT_PUBLIC_TRIKON_PUBLIC_KEY for the embeddable widget and NEXT_PUBLIC_DEMO_MODE for sample data. Keep the secret API key on the server; never expose it through a NEXT_PUBLIC variable.

Begin in demo mode to understand the navigation and data shapes. Then add your Trikon credentials and verify agents, phone numbers, call logs and outbound calling before introducing CRM entities.

2. Design the CRM around a unified customer record

The contact should be the centre of the product. Calls, messages, tasks and deals should reference the same contact ID instead of maintaining separate customer lists for each channel.

A practical first data model includes:

• contacts: name, phone numbers, WhatsApp number, email, owner, source, consent and lifecycle stage.
• companies: organisation details, domain, industry, account owner and linked contacts.
• deals: pipeline, stage, value, expected close date and next action.
• tasks: title, assignee, due date, priority, status and links to a contact, company or deal.
• interactions: a common activity record for voice calls, WhatsApp messages, notes, emails and meetings.
• channel records: call-specific fields such as duration and recording URL, plus WhatsApp-specific fields such as direction, delivery status and provider message ID.

Store channel-specific detail without fragmenting the customer history. A single timeline can then show that an AI voice call qualified a lead, a WhatsApp summary was sent and a sales task is due tomorrow.

3. Turn the Voice AI dashboard into a CRM module

Keep the repository’s server-side proxy pattern. The browser calls your Next.js routes, and those routes call the Trikon Voice API with the secret key. This reduces credential exposure and gives you one place to add access control, tenant checks, rate limits and audit logs.

Use agents to select the right calling workflow, phone numbers to identify the line being used, outbound calling to initiate a conversation and webhooks to update the CRM when the call changes state. When a call completes, upsert an interaction linked to the contact and store the outcome, duration and relevant metadata.

Then translate call outcomes into business actions. A qualified lead can move to the next pipeline stage. A requested callback can create a task. A support escalation can be assigned to an agent. A no-answer result can schedule another attempt or trigger a WhatsApp follow-up.

The starter’s call-log interface is also a useful base for a customer timeline. Replace a voice-only list with a polymorphic activity feed that can render calls, messages, tasks and notes using the same layout.

4. Add WhatsApp as a conversation channel

WhatsApp is not currently implemented in the starter repository, so treat it as a separate integration behind your own service layer. Connect an approved WhatsApp Business provider, receive inbound and delivery webhooks, and write every message to the interaction timeline.

Your WhatsApp module should support:

• inbound and outbound messages linked by provider message ID.
• conversation windows and approved message templates.
• delivery states such as queued, sent, delivered, read and failed.
• media metadata without exposing private asset URLs unnecessarily.
• contact consent, opt-outs and a complete audit trail.

Use an idempotency key for every webhook because providers may retry events. Verify webhook signatures, store the raw event for debugging and process the business update asynchronously. This prevents duplicate messages or tasks when the same event arrives more than once.

Useful automations include sending a WhatsApp summary after an AI call, asking a lead to confirm an appointment, sharing a payment or document link, and notifying the account owner when a customer replies. Always respect template, consent and regional communication rules.

5. Build task management into every workflow

Task management should not be a separate to-do page that users forget. Tasks should be created from customer events and remain visible inside the related contact or deal.

At minimum, give each task an owner, due date, priority, status, description and related record. Add created-by and completed-at fields for accountability. Useful views include My Tasks, Overdue, Due Today, Unassigned and tasks grouped by pipeline stage.

Event-driven task rules make the CRM valuable:

• If a voice call requests a callback, assign a timed follow-up to the contact owner.
• If a WhatsApp message remains unanswered, create a review task after the chosen service-level window.
• If a deal changes stage, generate the checklist required for that stage.
• If the AI detects an escalation or negative sentiment, create a high-priority task for a human.

Keep automation explainable. Show why each task was created and link back to the call or message that triggered it.

6. Create one activity timeline

A unified timeline is the heart of the CRM. Normalize each event into a small common shape: event type, timestamp, contact, owner, direction, summary, status and a reference to the channel-specific record.

Do not force every channel into one oversized table. Keep full call and message payloads in dedicated records, then project the fields needed for the timeline. This approach makes the interface simple while preserving detailed data for debugging and analytics.

Add search and filters for channel, owner, outcome, date and deal stage. The first useful dashboards are usually operational: overdue callbacks, unanswered conversations, calls by outcome, WhatsApp delivery failures and conversion by source.

7. Protect customer and communication data

A CRM combines identity, conversation and behavioural data, so security is part of the architecture—not a final checklist.

• Keep provider secrets server-side and rotate them.
• Verify webhook signatures and make webhook processing idempotent.
• Apply role-based access and tenant scoping to every query and mutation.
• Encrypt sensitive data, restrict recording access and define retention rules.
• Record consent, opt-outs and the lawful basis for outbound communication.
• Maintain an audit log for exports, ownership changes and sensitive actions.

8. Build the CRM in three releases

Release 1 — customer workspace: contacts, companies, owners, notes, the existing Trikon call-log experience and manual tasks.

Release 2 — connected conversations: outbound calls, Voice AI webhooks, WhatsApp inbound and outbound messages, a unified activity timeline and automatic follow-up tasks.

Release 3 — operations and growth: deals and pipelines, workflow rules, dashboards, permissions, imports, exports and integration monitoring.

This sequence gives users value early without hiding integration risk. Test each release with real contact ownership, duplicate phone numbers, webhook retries, time zones and opt-outs—not only perfect demo records.

A simple reference architecture

The Next.js application provides the CRM interface and server-side API routes. A relational database stores customers, tasks, deals and normalized interactions. Trikon supplies the Voice AI channel. Your WhatsApp Business provider supplies messaging. Webhook handlers translate channel events into CRM interactions, while a job queue runs retries, delayed follow-ups and workflow automation.

The most important boundary is the integration layer. UI components should read normalized CRM data instead of depending directly on a provider response. That lets you change a calling or messaging provider later without rebuilding the entire product.

Where to extend the repository

Preserve the existing Trikon API client, routes, hooks and TypeScript types. Add database-backed modules for contacts, tasks and interactions, then connect them to the existing calling and webhook flows. The current pages and components can be renamed or expanded into Voice, Contacts, Conversations, Tasks and Pipeline sections.

The repository uses a familiar Next.js structure, so a developer can progressively replace the demo store with persistent data, add authentication and build new API routes without discarding the working Voice AI examples.

Start building

Fork or clone the Trikon Voice AI Dashboard Starter at https://github.com/trikontech/voice-ai-example-dashboard, run it in demo mode and choose one real customer workflow. Connect Voice AI first, add the shared contact and interaction model, then layer WhatsApp and task automation onto the same timeline.

That produces a CRM shaped around how your team actually communicates—not a generic database with another set of unused fields.

Before adopting or redistributing the repository, review its current usage and licensing terms. A public GitHub repository is visible and clonable, but an explicit open-source licence defines broader permissions.