Best Haptik Alternative to Build AI Chatbots & Assistants in 2025

Are you wondering whether there’s an alternative to Haptik that can support broader automation goals while still delivering strong conversational experiences? 

Haptik is widely recognized as a sophisticated conversational AI solution used by enterprises to automate customer interactions, support workflows across WhatsApp, web, voice, and social channels, and help teams scale engagement with intelligent virtual assistants.

At the same time, many organizations are looking for platforms that go beyond chatbot responses and help integrate conversational intelligence into multi-step processes, actions, and outcomes such as:

• Generating structured insights, 
• Automating internal follow-ups, or 
• Connecting directly to business data. 

Knolli.ai is positioned in that space as an AI platform where teams can build, launch, and customize AI copilots that do more than reply. These copilots assist with real work by leveraging knowledge bases, integrations, and workflow triggers.

In the following sections, we’ll clearly explain what Haptik offers, highlight where teams might seek a different approach, and show how Knolli delivers contextual AI that helps users automate real business processes, all framed in simple, user-friendly terms.

Haptik is an enterprise-grade AI platform that enables organizations to build and deploy intelligent conversational agents and workflows using natural language understanding and automation. Its toolkit is designed to help teams deliver customer support, lead engagement, and transactional assistance across digital channels, with features tailored to real business use cases. 

• AI Agent Builder & Conversation Studio: Haptik includes a visual, no-code/low-code builder called Conversation Studio, which allows teams to design and train conversational workflows without heavy software engineering. It also provides pre-built smart skills and templates that help businesses go live faster for common support and engagement scenarios. ‍
• Omnichannel Engagement: Haptik’s agents can be deployed across popular customer touchpoints, including WhatsApp, web chat, Instagram, Facebook Messenger, SMS, and Google Business Messages, so brands can meet users on the platforms they already use.
• Intent Discovery & Intelligent Logic: The platform helps teams discover the most common customer intents by analyzing past support tickets and conversation logs. It also supports drag-and-drop workflow creation, quick replies, conversational UI elements, and proactive messaging to improve engagement and reduce friction.
• Voice Agent & Natural Language Understanding: Beyond text, Haptik supports voice-enabled AI agents that can understand and respond conversationally over calls. Its underlying technology uses natural language processing (NLP) to interpret user intent and deliver contextually relevant responses. ‍
• Analytics & Integrations: Haptik provides performance dashboards and insights so teams can monitor agent effectiveness, identify common user questions, and optimize over time. It also integrates with CRM systems, live chat tools, and backend services, enabling escalation to human agents or the enrichment of workflows when needed.
• Industry Templates & Use Case Support: The platform offers solutions and templates for a range of industries, from retail and travel to finance and telecom, helping businesses tailor conversational flows to their specific needs without starting from scratch.

Even though Haptik is a well-established conversational AI platform with strong automation and engagement capabilities, some teams find certain aspects limiting as their needs evolve beyond basic chatbot and support automation functionality. 

Below are common reasons businesses look for Haptik alternatives.

1. Complexity with Highly Customized Logic

Users report that while the flow builder is intuitive for standard use cases, it can feel restrictive when creating deeply customized logic or complex workflows. This can require technical back-end support or workarounds that slow down iteration.

2. Integration Challenges for Advanced Scenarios

Although Haptik supports integrations with CRM and backend systems, some customers face additional work to achieve seamless escalation or detailed data synchronization for complex enterprise use cases. This can make tightly coupled workflow automation harder to achieve without developer resources.

3. Handling Open-Ended or Ambiguous Queries

Reviewers and third-party assessments note that some conversational tasks outside predefined flow paths, especially poorly structured or highly open-ended queries, may not perform as smoothly, requiring additional training and refinement.

4. Multilingual Scaling and Testing Overhead

While Haptik provides support in 100+ languages, expanding across multiple languages at scale may require extensive training data and careful testing to ensure consistent accuracy across diverse user inputs.

5. Integration Setup and Unforeseen Technical Work

Some businesses have encountered integration issues during initial setup, particularly when synchronizing with internal systems or external APIs. While support teams typically help resolve these issues, the process can take additional time and technical effort. 

These practical considerations, especially around complex automation, tight system integration, and conversational flexibility, can lead growth-oriented organizations to explore platforms that handle advanced workflow orchestration and deeper, context-aware actions more naturally.

Knolli is designed with that broader use case in mind , enabling users to not only automate conversations but to leverage internal knowledge, connect systems and data sources, and create tailored AI copilots that support both internal and customer-facing functions.

• Custom AI Copilot Creation from Your Own Context: Knolli allows teams to convert internal information, such as documents, guides, datasets, or proprietary knowledge, into interactive AI copilots that can answer questions and support tasks based on your own content. This goes beyond pre-configured conversational paths and gives teams a way to operationalize their own knowledge without needing deep technical expertise.
• Rapid Deployment: Knolli’s interface is designed so users can quickly configure and launch AI copilots, including onboarding data sources and connections that the copilots reference. This helps teams introduce new AI-driven capabilities fast, even when engineering resources are limited.
• Flexible Integrations with Tools and Data: Knolli supports integrations with CRMs, storage systems, databases, and live data sources so your AI copilots can act with real knowledge and updated context from your systems , enabling assistants that don’t just respond conversationally, but reference real business data.
• Templates and Frameworks for Diverse Use Cases: Knolli offers ready-to-use templates and pre-built copilot patterns that help organizations jumpstart common AI tasks, such as sales assistance, customer support workflows, or document-based Q&A experiences, while maintaining the flexibility to customize them for specific needs.
• Advanced Features for Scaling AI Work: Knolli includes features such as multi-agent support (running multiple specialized AI agents under a single copilot), custom branding, enterprise-grade security, and analytics dashboards to help teams understand how their AI assets are performing and where they add value. 

According to the official description of Haptik’s offerings, its primary documented strengths lie in building conversational AI agents and intelligent virtual assistants that engage users, support customers, and handle workflows across channels such as WhatsApp and websites.

Knolli extends this by focusing on knowledge-driven AI copilots that connect to your business data and automate workflows beyond support dialog alone, enabling teams to inject AI into internal knowledge tasks, sales enablement, research processes, and more, all anchored in your own structured content and tools.

Imagine a support leader at a tech company launching a major product update while handling a spike in customer queries, internal knowledge requests, and complex follow-ups in the same week:

• With Haptik, conversational AI agents engage customers across WhatsApp, web, and messaging channels, providing automated answers to product questions, qualifying leads, and routing complex cases to live agents.
  Teams see improved engagement and faster responses, and the automated routing handles routine interactions with minimal supervision. However, complex follow-ups, such as summarizing internal documents, extracting detailed insights from technical guides, and coordinating multi-step operational tasks across systems, still require human coordination beyond the conversational layer.
  
• With Knolli, Conversations across text and voice also receive intelligent replies, but the interaction doesn’t stop at answering questions. Knolli’s AI copilots can leverage your own knowledge bases, uploaded content, and integrated tools to generate structured summaries, trigger action workflows, and retrieve precise details from internal documents in real-time.
  This means a customer question about a policy can automatically produce a concise summary from the product manual, initiate ticket creation, notify the support team, and help generate follow-up tasks without manual handoffs, all within a single, cohesive flow.

When comparing AI platforms for modern business needs, conversational AI solutions like Haptik shine in automating customer engagement across messaging and voice channels, handling routine inquiries, and supporting 24/7 interactions with intelligent virtual assistants.

However, platforms built around AI copilots that connect directly to your own knowledge and workflow systems can go beyond conversation to deliver context-aware automation, structured insights, and seamless task execution, turning static content like guides and datasets into interactive, actionable tools without heavy coding. Knolli’s design as an AI copilot platform helps teams bridge conversational AI with real business actions, making it a compelling alternative for organizations seeking deeper automation and knowledge-driven outcomes.

How should a business choose between conversational AI and workflow automation platforms?

Choosing depends on goals: for customer interaction automation, conversational AI with strong NLU and omni-channel support is key; for internal task orchestration and automation, a platform with knowledge integration, workflow triggers, and task outputs may deliver higher operational value. Decision criteria include use case complexity, integrations, and action automation depth.

What are the practical considerations before implementing conversational AI?

Important factors include natural language understanding quality, multilingual capabilities, ease of deployment, integration with existing systems (CRM, helpdesk), analytics visibility, and ongoing optimization. Evaluating training complexity, data governance, and live agent handoff ensures the platform meets both support and business process needs.

What’s the difference between conversational AI and AI copilots when choosing Haptik alternatives?

Conversational AI focuses on engaging in dialogue, understanding user messages, and responding to them across channels. AI copilots go beyond chat by embedding into workflows, accessing live data, generating insights, and automating tasks based on context. Choosing between them depends on whether you want interaction only or interaction plus actionable productivity.