AskMe is a SaaS platform that lets you create AI agents that respond to customers on Slack, Teams, Google Chat, Discord, Telegram, GitHub, Linear, and WhatsApp — from a visual dashboard, live in minutes.

How much does it cost?

We offer two plans — Starter and Pro — both 50% off during the beta. Your beta price is locked in for life, even after launch. For larger organizations, our Enterprise plan includes dedicated support and SLA.

Do I need technical skills?

AskMe is built for business teams. If you can write an email, you can build an AI agent. Our visual editor guides you through every step.

How is my data handled?

All data is encrypted at rest and in transit. We never use your customer data to train our models. You own your data and can export it at any time.

When does the beta start?

The beta is live now. Sign up to get instant access and start building your first AI agent today.

What is the difference between an AI agent and a chatbot?

Traditional chatbots follow rigid, pre-scripted rules and can only handle questions they were explicitly programmed for. AskMe builds true AI agents — autonomous assistants powered by large language models that understand context, reason through problems, and deliver natural, human-like conversations without requiring you to map out every possible scenario.

What exactly is an AI agent, and why would I need more than one?

An AI agent is an autonomous assistant trained on your data that holds natural conversations on your messaging channels. You might want multiple agents for different purposes — customer support on WhatsApp, IT help on Slack, sales qualification on Telegram. Each has its own personality, knowledge base, and channels.

What happens when I reach my message limit?

Your agents pause until the next billing cycle. You'll receive a notification before hitting the limit so you can upgrade if needed. Built-in spam detection protects your quota from abuse.

What if someone spams my AI agent?

AskMe includes built-in rate limiting and spam detection on every channel. Automated abuse is blocked before it reaches your agent, protecting your message quota.

How do I train my AI agent with my own data?

Simply upload your content — documents, FAQs, website URLs, or PDFs — through our visual editor. The agent uses Retrieval-Augmented Generation (RAG) to ground every response in your verified data, so it answers based on your actual content rather than making things up. You can update the knowledge base at any time and changes take effect immediately.

What happens when the AI agent can't answer a question?

When your AI agent encounters a question it can't confidently answer, it doesn't guess or hallucinate. Instead, it gracefully acknowledges its limitation and can be configured to escalate — for example, by collecting contact details for follow-up, redirecting to a resource, or handing off to a human team member on the same channel.

Can I customize the AI agent's personality and tone of voice?

Yes. AskMe lets you fully define your agent's personality, tone, and communication style through the visual editor. Set it to be formal or casual, warm or efficient, technical or plain-spoken — whatever matches your brand voice. You can also define guidelines for how the agent introduces itself and what boundaries it should respect.

Which messaging platforms does AskMe support?

AskMe supports 8 messaging platforms out of the box: WhatsApp, Slack, Discord, Telegram, Microsoft Teams, Google Chat, GitHub, and Linear. Build your AI agent once, then deploy it across any combination of these channels from a single dashboard.

Can I deploy one AI agent on multiple channels at the same time?

Absolutely. AskMe follows a build-once, deploy-everywhere approach. Create a single AI agent with one knowledge base and one set of behavior rules, then activate it on as many channels as you need — all simultaneously. Updates to the agent's knowledge or behavior are reflected instantly across every connected channel.

How long does it take to set up an AI agent?

Most users have their first AI agent live and responding to messages within minutes. Our visual editor guides you through each step: name your agent, upload your knowledge base, choose your channels, and deploy. The visual editor handles the rest.

Is AskMe GDPR compliant?

Yes. All data is encrypted at rest and in transit. We never use your data or your customers' conversations to train AI models. You retain full ownership and can request deletion at any time. Our infrastructure is designed to meet the requirements of the GDPR and the EU AI Act.

What use cases can I build with AskMe?

Common use cases include customer support automation, internal team assistants (HR, IT help desk), community management on Discord or Telegram, sales and lead qualification on WhatsApp, developer tooling with GitHub issue triage, and project management support via Linear. You can build any conversational agent that benefits from your custom knowledge base.

Does AskMe support multiple languages?

Yes. AskMe's AI agents can understand and respond in over 100 languages — including English, Italian, Spanish, French, German, Portuguese, Arabic, Chinese, Japanese, and many more. The agent automatically detects the language of incoming messages and responds in the same language, with no additional configuration required.

No-Code vs Custom-Built AI Agents: Which Is Right for You?

When you decide to deploy an AI agent for your business, one of the first decisions you face is how to build it. Do you use a no-code AI agent builder like AskMe Studio, or do you invest in a custom-built solution developed by your engineering team? Both approaches have real strengths, and the right choice depends on your specific situation. This guide breaks down the trade-offs to help you decide.

Understanding the Two Approaches

No-Code AI Agent Builders

No-code platforms provide visual interfaces, pre-built integrations, and managed infrastructure for creating AI agents. You configure behavior, upload knowledge bases, and connect messaging platforms without writing code. The platform handles the underlying AI models, infrastructure, scaling, and maintenance.

Custom-Built AI Agents

Custom-built agents are developed from scratch by your engineering team or a contracted development firm. This typically involves selecting and integrating LLM APIs, building natural language processing pipelines, developing platform integrations, setting up infrastructure, and maintaining the entire system ongoing.

Comparison: Key Factors

Time to Deploy

This is where the difference is most dramatic:

No-code — Minutes to hours. Create an account, upload your knowledge base, configure behavior, connect your channels, and you are live
Custom — Weeks to months. Requirements gathering, API integration, pipeline development, testing, infrastructure setup, and deployment cycles add up quickly

For businesses that need AI support capabilities now, not next quarter, no-code platforms offer an unmatched speed advantage.

Cost

No-code — Predictable subscription pricing. No upfront development costs, no infrastructure expenses, no specialized hiring
Custom — Significant upfront investment. AI/ML engineers command high salaries, cloud infrastructure costs add up, and ongoing maintenance requires dedicated resources. A typical custom AI agent project costs tens to hundreds of thousands of dollars before it handles its first conversation

Flexibility and Customization

No-code — Highly configurable within the platform's capabilities. You can customize knowledge bases, behavior, tone, escalation rules, and channel configuration. Some advanced customizations may be limited by what the platform supports
Custom — Unlimited flexibility. You control every aspect of the system. If you can code it, you can build it. This matters for highly specialized use cases or deep integrations with proprietary systems

Maintenance and Updates

No-code — The platform handles infrastructure, model updates, security patches, and scaling. You focus on content and configuration
Custom — You own everything. When LLM providers update their APIs, when messaging platforms change their integrations, when security vulnerabilities emerge, your team must respond. This ongoing burden is often underestimated at project inception

Multi-Platform Support

No-code — Platforms like AskMe Studio provide built-in integrations for multiple messaging platforms. Deploy to WhatsApp, Slack, Discord, Teams, and more with configuration changes, not code
Custom — Each platform integration must be built and maintained separately. WhatsApp, Slack, Discord, Teams, Telegram, Google Chat, GitHub, and Linear each have different APIs, authentication flows, and message formats. This multiplies development and maintenance effort

Scaling

No-code — Managed platforms handle scaling automatically. Whether you have 10 conversations or 10,000 per day, the platform adjusts
Custom — Scaling must be engineered. Load balancing, queue management, database scaling, and failover all require planning and implementation

When No-Code Is the Right Choice

No-code AI agent builders are the best fit when:

You need to deploy quickly and cannot wait months for development
Your use case is customer support, community management, internal help, or similar standard scenarios
You want multi-platform deployment without building each integration
Your team does not include AI/ML engineers
You prefer predictable costs over large upfront investments
You want to focus on content and strategy rather than infrastructure
You are a small to medium business or a startup

When Custom Is the Right Choice

Custom-built AI agents make sense when:

Your use case is highly specialized and no existing platform supports it
You need deep integration with proprietary internal systems
Regulatory requirements mandate on-premises deployment or specific data residency
You have an experienced AI/ML engineering team with available capacity
Your competitive advantage depends on proprietary AI capabilities
You operate at a scale where managed platform costs exceed self-hosted infrastructure

The Hybrid Approach

Many organizations find that a hybrid approach works best. Start with a no-code platform to validate the concept, prove ROI, and start serving customers immediately. If you identify specific needs that exceed the platform's capabilities, you can then invest in custom development for those specific components while keeping the no-code platform for standard use cases.

This approach minimizes risk because you are making custom investment decisions based on real data about what your business actually needs, not assumptions.

Common Misconceptions

No-Code Means Low Quality

This is false. Modern no-code platforms use the same underlying AI models and natural language processing as custom solutions. The quality of responses depends primarily on the quality of your knowledge base and configuration, not whether you wrote the integration code yourself.

Custom Always Provides Better Performance

Not necessarily. Well-engineered no-code platforms often outperform hastily-built custom solutions because they represent years of optimization and thousands of deployment learnings. A custom solution is only better if your team has the expertise and time to make it better.

No-Code Is Only for Small Businesses

Many enterprises use no-code platforms for AI agents, particularly for standard use cases like customer support and internal help desks. The speed and reduced maintenance burden are valuable at any scale.

Making Your Decision

The honest truth is that for 80-90% of businesses deploying AI agents for customer support, community management, or internal help desks, a no-code platform like AskMe Studio is the faster, cheaper, and often better choice. The remaining 10-20% with truly specialized needs will benefit from custom development.

If you are unsure which category you fall into, start with no-code. You will be live in minutes, start learning from real interactions immediately, and can always evaluate custom options later if needed. The worst case is that you spent a few hours setting up something useful while figuring out your long-term strategy.