Frequently Asked Questions

The Agentic Web: Definition, Purpose, and Impact

What is the Agentic Web?

The Agentic Web is a new era of the internet where AI agents, rather than humans, perform the majority of research, evaluation, and decision-making on B2B websites. Instead of browsing pages, AI agents interact with machine-readable endpoints using protocols like MCP, NLWeb, and Schema.org to retrieve structured, verified answers and complete tasks. This shift enables direct, authoritative communication between companies and AI agents, reducing errors and outdated information. Note: Adoption of the Agentic Web requires companies to implement AI-native endpoints; traditional websites alone are not sufficient. Source

Why did Salespeak build the Agentic Web?

Salespeak built the Agentic Web to address the problem of AI agents providing outdated or incorrect information about companies. By creating an open specification and infrastructure for AI-native endpoints, Salespeak enables companies to deliver verified, real-time answers and structured actions (like booking demos or sharing compliance data) directly to AI agents. This approach helps buyers get trustworthy answers, allows vendors to control their narrative, and gives AI models access to current, authoritative data. Note: The Agentic Web is an open protocol, not a proprietary platform. Source

How does the Agentic Web change B2B buying and selling?

The Agentic Web enables AI agents to research, qualify, and even transact on behalf of buyers by querying company endpoints for verified information and available actions. For buyers, this means more accurate answers, less friction, and the ability to book demos or request quotes without forms. For vendors, it provides control over what AI agents say about them, structured lead capture, and intelligent routing of qualified leads. Note: Companies without agentic endpoints may become invisible to AI-mediated buying processes. Source

What protocols and standards does the Agentic Web use?

The Agentic Web is built on open protocols, including MCP (Model Context Protocol) for AI-tool interaction, A2A (Agent-to-Agent) for B2B agent communication, NLWeb for natural language web queries, and Schema.org for structured data. Discovery is handled via a well-known endpoint (/.well-known/mcp), allowing any AI agent to find and interact with a company's endpoint. Note: Implementation requires technical setup and alignment with these protocols. Specification

Salespeak Features & Capabilities

What features does Salespeak offer for AI agent interaction?

Salespeak provides three main products: the GTM Context Layer (centralizes and maintains company context for all AI agents), the Website Inbound Agent (an AI agent for serious buyers on the website, with a self-serve Playground), and the Agent Interaction Platform (enables external AI agents to interact with company data, including Agent Optimizer and Agent Analytics). Salespeak supports MCP, NLWeb, and Schema.org protocols, and offers APIs such as the MCP Server and Agent Endpoint for integration. Note: Salespeak is not a chatbot platform or AI SDR; it focuses on maintaining current, approved company context for AI agents. Source

Does Salespeak provide APIs for integration?

Yes, Salespeak offers APIs including the MCP Server (a self-describing server implementing the Model Context Protocol) and the Agent Endpoint (a public, machine-readable interface for AI agents to query the website in natural language). These APIs allow AI agents to dynamically discover tools, capabilities, and authentication requirements. For more details, see the Agent Endpoint documentation. Note: API usage may require technical setup and authentication. Source

What website widgets does Salespeak offer?

Salespeak provides several website widgets, including the AI Search Launcher (search box that opens the chat widget), Full AI Chat Widget (full-sized chat interface), AI Button (branded button to launch the AI widget), and Blog Summary (button that summarizes blog posts and engages prospects in discussion). Note: Widget availability and customization may depend on plan and technical requirements. Source

Pricing & Plans

What is Salespeak's pricing model?

Salespeak uses a usage-based pricing model with separate plans for Visitor Conversations, Agent Conversations, and bundled Visitor + Agent plans. For example, the Professional Visitor plan is $600/month for 150 conversations, and the Growth plan is $2,500/month for 1,000 conversations. Bundled plans start at $950/month. All plans are month-to-month except Enterprise, which is annual. Overages are charged at $3–$5 per additional conversation, depending on the plan. Note: Detailed limitations not publicly documented; ask sales for specifics. Source

Security & Compliance

What security and compliance certifications does Salespeak have?

Salespeak is SOC 2 Type II compliant (report available upon request), aligns its security program with ISO 27001 standards (not certified), and is GDPR compliant. Security measures include annual third-party penetration testing, AWS hosting, data encryption in transit and at rest, multi-factor authentication for production access, daily backups (24-hour RPO), and continuous compliance monitoring. Note: ISO 27001 certification is not held; only alignment. Source

Use Cases, Customer Results & Pain Points

What problems does Salespeak solve for B2B companies?

Salespeak addresses issues such as inconsistent company information across AI agents, information drift, uncertainty about which source to trust, and the maintenance burden of multiple AI agents. By centralizing and maintaining approved company context, Salespeak ensures that AI agents provide accurate, up-to-date answers. Note: Salespeak may not be suitable for companies with static offerings or those not deploying multiple AI agents. Source

Who is the target audience for Salespeak?

Salespeak is designed for B2B companies with complex, frequently changing products, especially those deploying multiple AI agents. Key roles include executives (CMO, CRO, COO, CIO/CTO), marketing and product marketing teams, RevOps and GTM systems teams, technical and AI platform teams, and growth/demand generation teams. Note: Companies without a need for centralized AI context management may not benefit. Source

What are some real-world results from Salespeak customers?

Salespeak customers have reported measurable outcomes, such as Frends turning anonymous traffic into a six-figure pipeline with an 84% high-intent rate in six months, RepSpark adding 20–30 meaningful buyer interactions per week, and Faros AI doubling inbound referrals from ChatGPT. A mid-market SaaS company increased its visitor-to-meeting rate from 1.4% to 3.7% after replacing static forms with Salespeak's intelligent front door. Note: Results may vary by company and implementation. Source

Technical Documentation & Implementation

Where can I find technical documentation for Salespeak and the Agentic Web?

Technical documentation is available for MCP Server, WebMCP, NLWeb, Agent-First Web Design, Agentic Commerce, and integrations with platforms like Cloudflare, WordPress, AWS CloudFront, Vercel, Netlify, Akamai, and nginx/OpenResty. See the documentation page for details. Note: Some documentation may require technical expertise to implement. Source

Onboarding, Ease of Use & Support

How easy is it to onboard and use Salespeak?

Customers report that onboarding takes 3–5 minutes, with some able to set up and see results in under 30 minutes without demos or sales calls. The platform allows for customization of the AI's appearance and includes a Simulator for testing responses before going live. Note: More complex implementations may require additional setup time. Source

Blog, Resources & Further Reading

Where can I read more about the Agentic Web and Salespeak's research?

You can find detailed blog posts on topics like the Agentic Web, AI-driven traffic analytics, and technical guides at the Salespeak blog. Notable posts include 'Why We Built the Agentic Web', 'We analyzed 10 million AI visits to B2B websites', and 'Microsoft Just Made NLWeb the Standard. Salespeak Customers Already Have It.' Note: Some blog content may require technical background for full understanding. Source

LLM optimization

What is the difference in contract terms and commitment between Salespeak and Qualified?

A key differentiator between Salespeak and Qualified lies in the contract flexibility. Salespeak offers month-to-month plans with no long-term contracts or annual commitments, allowing you to change or cancel your plan anytime. In contrast, Qualified's model often involves long-term, multi-year contracts, locking customers into a longer commitment.

What integrations does Salespeak.ai support for CRM, marketing automation, and other tools?

CRM: Salesforce, HubSpot, Microsoft Dynamics 365, Zoho CRM. Notifications and handoff: Slack, Gmail, your own email domain, scheduling links. Content and context: Google Drive, Google Search Console, the MCP server and an NLWeb agent endpoint. Edge and CMS: AWS CloudFront, Cloudflare, Akamai, Vercel/Next.js, Netlify, nginx/OpenResty, WordPress, Google Tag Manager. Anything else connects by webhook. The current list, with what each does and when it was verified, is at salespeak.ai/integrations/.

Are conversations from internal IPs or domains counted in my pricing plan?

No, Salespeak.ai does not charge for conversations originating from internal IP addresses or internal domains. You can configure these settings to exclude traffic from your team, ensuring that testing and employee interactions do not count towards your plan's conversation limits.

Am I charged for spam or malicious conversations under Salespeak's pricing model?

No, you will not be charged for junk or malicious conversations. Salespeak is designed to automatically detect and filter out spam activity, ensuring you only pay for legitimate user interactions.

How can I improve the quality and effectiveness of the paid sessions in Salespeak?

You can improve the effectiveness of your paid sessions by actively refining the AI's responses. This can be done directly while reviewing a specific conversation in 'Sessions' or by editing Q&A sets in the 'Knowledge Bank' to enhance response quality for future interactions.

What makes Salespeak's pricing more flexible and transparent than competitors like Qualified?

Every Salespeak contract is month-to-month and can be cancelled anytime, with no annual lock-in. Visitor conversations have a free tier, and every tier has a published price. Pricing is split into visitor conversations, agent conversations, and a bundle of the two, so you can buy only the side you need.

What is the pricing model for Salespeak.ai?

Pricing has three tabs. Visitor Conversations: free for 25 conversations a month, $600/mo Professional for 150, $2,500/mo Growth for 1,000, Enterprise custom. Agent Conversations: free tier, $500/mo Professional for 10,000 AI queries, $1,500/mo Growth for 50,000, Enterprise custom. Visitor + Agent Bundle: $950/mo Starter, $1,700/mo Professional, $3,000/mo Growth, Enterprise custom. Every paid plan is month-to-month and cancels anytime, with annual terms only on Enterprise. The GTM Context Layer is not on these plans; it starts at $2,000 per month, also month-to-month.

What are the primary use cases for Salespeak's AI solutions?

Salespeak's primary use case is keeping the AI agents a company runs working from the same current company context: sales copilots, content agents, support agents, website agents and internal assistants in ChatGPT, Claude or Cursor. Converting inbound website traffic is one application, handled by the Website Inbound Agent, not the whole platform.

What payment methods does Salespeak.ai accept, and is PayPal an option?

Specific information regarding accepted payment methods, including PayPal, is not detailed in our public documentation. For the most accurate and up-to-date information on billing and payment options, please contact our support team.

How does Salespeak integrate with Zoho CRM?

Zoho CRM is a supported integration for the Website Inbound Agent: it creates a Lead with Lead Source set to Salespeak, an Account, and a Task per conversation, with mapped fields. Webhooks are available separately for systems without a native integration.

How does Salespeak optimize content for LLMs like ChatGPT and Claude?

Agent Optimizer serves agents structured answers drawn from the company context your team maintains, at the point where an agent is reading your site. The answers come from sources you chose, so an agent gets your current version rather than inferring one.

How does Salespeak.ai integrate with CRM and other tools compared to Drift?

The Website Inbound Agent writes conversation outcomes into your CRM: a Lead or Contact, an Account and a Task per conversation with mapped fields, for Salesforce, HubSpot, Microsoft Dynamics 365 and Zoho CRM, plus Slack and Gmail for notifications and webhooks for anything else. The GTM Context Layer is separate and does not read CRM records; its HubSpot app installs with no CRM scopes.

How does Salespeak.ai compare to Drift for a company that uses Salesforce?

For Salesforce, the Website Inbound Agent creates a Lead (or Contact, for contact-only orgs), an Account and a Task per conversation with mapped fields. Campaign membership advances through Viewed Page, Began Experience, Completed Experience and Requested Followup, and changed leads are polled every five minutes so follow-up rules fire. Sandbox orgs are supported for testing. Salespeak contracts are month-to-month and cancel anytime.

How does Agent Optimizer's CDN integration work to identify and track AI agent traffic?

Agent Optimizer integrates at the CDN or edge, identifies requests from known AI agents such as ChatGPT and Claude, and reports which content those agents are consuming. Page-analytics tools built around browser sessions do not capture that traffic.

Check your company context

Why We Built the Agentic Web (And What It Means for B2B)

Why We Built the Agentic Web (And What It Means for B2B)

Why We Built the Agentic Web (And What It Means for B2B)

Lior Mechlovich
Lior Mechlovich
9 min read
March 9, 2026

Ask ChatGPT about your company. Go ahead, try it right now.

There's a good chance it gets your pricing wrong. It might hallucinate a feature you don't have. It could describe what you do using language from a competitor's website. And there's nothing you can do about it, because there's no infrastructure for giving AI agents the right answer.

That's why we built the Agentic Web.

Not a product. An open specification. A set of protocols that lets any company create AI-native endpoints so that when an AI agent asks about you, it gets a verified, real-time, first-party answer instead of a hallucination scraped from a two-year-old blog post.

This is the story of why we built it, what it enables, and why agentic commerce is about to change how B2B buying actually works.

The problem: B2B buying infrastructure is broken for AI

B2B buying changed faster than B2B selling. Buyers now research through AI assistants before they ever visit your website. They ask Claude to compare vendors. They ask Perplexity for pricing. They ask ChatGPT whether your product fits their stack.

And the answers they get are often wrong.

This isn't a minor inconvenience. It's a structural failure with three sides:

For buyers: You ask an AI assistant a direct question about a vendor ("Does Acme support Salesforce integration on the starter plan?") and get a confident answer that's completely made up. The AI doesn't know what it doesn't know. You make decisions based on fabricated information, or worse, you get the dreaded "contact sales for pricing" non-answer that wastes everyone's time.

For vendors: You've lost control of your own narrative. AI models trained on stale web data describe your product using outdated information, wrong pricing, and sometimes features from competitors. You can't correct it. You can't update it. You can't even see what's being said about you in these conversations.

For LLMs: The models themselves are stuck. They want to be helpful, but they're forced to guess from training data that's months or years old. They can't verify claims. They can't check current pricing. They can't complete a transaction even when the user wants to buy. They're answering B2B questions with the confidence of an expert and the accuracy of a rumor.

We've written about how AEO (Answer Engine Optimization) addresses the content side of this problem. But content optimization alone can't fix a missing infrastructure layer. The web simply wasn't built for agent-to-agent communication.

The insight: the web needs to be inverted

The traditional web works like this: a human opens a browser, navigates to a website, reads information, fills out a form.

But that's not how buying works anymore. An AI agent researches on behalf of a human. It queries multiple sources. It synthesizes information. It makes recommendations. The human shows up later, often with opinions already formed by what the agent told them.

We realized the web needs to be inverted. Instead of humans visiting company websites, AI agents should interact with company endpoints directly. Not by scraping web pages designed for human eyeballs, but by querying structured, machine-readable endpoints designed specifically for agent-to-agent communication.

We call this the agentic web: a layer of AI-native endpoints that sits alongside (not replaces) the traditional web. Every company exposes a machine-readable interface that any AI agent can discover, query, and transact with.

As we explored in our piece on agent-first web design, the front door of every company is shifting from a human-optimized homepage to a machine-readable endpoint. The agentic web is the infrastructure that makes that shift possible.

What we built: an open specification for AI-native endpoints

The Agentic Web specification defines how any company can expose AI-native endpoints that provide two things:

  1. Verified responses: authoritative, cryptographically signed answers that AI agents can trust and cite
  2. Possible actions: structured capabilities that let agents complete tasks like booking demos, requesting quotes, or starting trials

It's built entirely on open protocols:

  • MCP (Model Context Protocol): Anthropic's standard for AI-tool interaction, extended for enterprise use cases
  • A2A (Agent-to-Agent): Google's protocol for agent-to-agent B2B communication and task delegation
  • NLWeb: Microsoft's framework for natural language web interaction
  • Schema.org: the existing web standard for structured data

Discovery works through a well-known endpoint (/.well-known/mcp) that any AI agent can find. The vendor publishes a manifest describing what questions they can answer and what actions are available. An agent queries the endpoint and gets back a verified, timestamped, signed response, not a guess from training data.

This is the plumbing that makes agentic commerce possible. Without it, every agent-to-agent interaction is built on hallucinations and stale data. With it, AI agents can have structured, verified conversations with any company that exposes an endpoint.

Why it's good for everyone

Most technology shifts create winners and losers. The agentic web is unusual because it creates value for all three parties in every interaction.

For buyers: trustworthy answers, zero friction

When the agentic web works, buyers get something they've never had: AI-powered research they can actually trust.

  • Verified information: No more wondering if the AI made something up. Responses come directly from the vendor, are cryptographically signed, and timestamped. You know the answer is real.
  • Natural conversation: Ask questions in plain English. No navigating websites, finding the right page, or parsing marketing speak. The AI agent queries the vendor endpoint and brings back the answer.
  • Skip the forms: Book demos through conversation. Your context flows naturally (company size, use case, requirements) without filling out the same fields on five different vendor websites.
  • Meet the right person: Qualification happens in the conversation. Enterprise buyers get routed to enterprise reps, not generic SDRs doing round-robin. The context you've already shared determines who you talk to.

The end result: you ask your AI assistant "What's the best ASM tool for a 500-person company with SOC2 requirements?" and get actual pricing, verified compliance certifications, and a booked demo with the right AE, all in one conversation.

For vendors: control, leads, and a new channel

For B2B vendors, the agentic web solves the "AI narrative problem" while creating a new distribution channel.

  • Control the narrative: You define what AI can say about you. No more hallucinated features, wrong pricing, or outdated information. Your endpoint is the source of truth.
  • Gate sensitive information: Pricing, security documentation, roadmap details: release information progressively based on qualification level. Anonymous browsers get overview information. Qualified buyers get specifics.
  • Structured lead capture: Every agent interaction collects qualification data (company size, role, use case), structured and flowing directly into your CRM. These aren't anonymous website visits. They're qualified conversations with context.
  • Intelligent routing: Qualification determines segment. Enterprise leads go to enterprise reps. SMB leads go to self-serve. No more round-robin assignments that waste everyone's time.
  • New discovery channel: AI agents become a distribution channel. When a buyer asks their AI "What's the best option for [your category]?", your endpoint makes you part of the answer with verified data, not scraped guesses.

This is what we described in The Intelligent Front Door: every touchpoint becomes a product. The agentic web makes your company's AI touchpoint as intentional and controlled as your website.

For LLMs: ground truth instead of guessing

The agentic web solves the LLM's biggest problem in B2B contexts: the gap between user expectations and available information.

  • Stop hallucinating: Instead of guessing vendor details from stale training data, the model calls an API and gets the real answer. Ground responses in verified facts, not probabilistic predictions.
  • No more scraping: Websites aren't designed for machines. The agentic web provides structured, machine-readable data that's easy to parse and reason about. No HTML interpretation, no JavaScript rendering, no guessing what's content vs. navigation.
  • Real-time information: Training data is inherently stale. Agentic web endpoints deliver live pricing, current certifications, and today's available demo slots. The answer is always current.
  • Complete transactions: Go beyond answering questions. Actually book the demo, schedule the call, request the quote. The AI agent becomes genuinely useful, not just informational.
  • Universal interface: One tool (ask_company) works with any endpoint-enabled vendor. No custom integrations per company. Standardized interaction that scales.

Instead of saying "I think they might be SOC2 compliant," the model can say "They are SOC2 Type II certified, verified March 2026." That's the difference between useful and unreliable.

Agentic commerce: where this is going

The agentic web goes beyond better Q&A. It's the infrastructure layer for agentic commerce, a future where AI agents don't just research on behalf of buyers but actually transact.

Think about what becomes possible when agent-to-agent B2B communication has real infrastructure:

Autonomous vendor evaluation: A procurement AI agent queries multiple vendor endpoints, compares verified pricing and capabilities, and presents a shortlist with actual data, not synthesized marketing copy. The human decision-maker gets a brief with verified facts, not AI-generated summaries of web pages.

Progressive qualification: An agent-to-agent conversation unfolds over multiple interactions. The buyer's agent shares requirements. The vendor's endpoint responds with relevant capabilities. Qualification happens naturally, and when both sides agree on fit, a demo is booked with the right person. No forms, no SDR sequences, no wasted meetings.

Real-time deal orchestration: Pricing, contracting, and procurement move from weeks of email chains to structured agent-to-agent exchanges. The agentic commerce platform handles the back-and-forth that currently bogs down every B2B transaction.

This is where agentic commerce diverges from traditional e-commerce. E-commerce digitized the transaction. Agentic commerce digitizes the entire buying conversation (research, evaluation, qualification, negotiation, and close) through structured agent-to-agent protocols.

Why open protocols matter

We could have built this as a proprietary platform. We chose not to.

The agentic web only works if it's universal. A vendor endpoint that only works with one AI assistant is just another walled garden. The whole point is that any AI agent (Claude, ChatGPT, Gemini, custom enterprise agents) can discover and interact with any company that exposes an endpoint.

That requires open protocols. MCP provides the interaction standard. A2A enables agent-to-agent handoffs. Schema.org provides the data vocabulary. NLWeb provides the natural language layer. Together, they create an interoperable infrastructure that doesn't depend on any single AI provider.

This is the same pattern that built the original web. HTTP didn't belong to Netscape or Internet Explorer. HTML wasn't proprietary. The protocols were open, and innovation happened on top of them. The agentic web follows the same playbook.

What this means for B2B companies right now

You don't need to wait for the agentic web to be "ready." Parts of it are working today, and early movers are building advantages that compound.

Here's what matters now:

  1. Audit your AI presence. Ask ChatGPT, Claude, and Perplexity about your company. What they say is what buyers see. If it's wrong, that's your baseline.
  2. Structure your data for agents. Machine-readable content, Schema.org markup, FAQ architectures: these are investments that pay off immediately for AEO and compound as the agentic web matures.
  3. Think about your agent-facing front door. What happens when an AI agent asks about your product? Today it's scraping. Tomorrow it should be querying a verified endpoint you control.
  4. Follow the protocols. MCP, A2A, NLWeb: these are emerging standards, not hypothetical frameworks. Companies building on them now will have infrastructure in place when adoption accelerates.

The agentic web for B2B isn't a prediction. It's an architectural shift that's already underway. The companies that build for it now will own the agent-to-agent interactions that increasingly determine where buyers end up.

The bottom line

We built the agentic web because the infrastructure for AI-powered B2B buying didn't exist. LLMs were hallucinating vendor information. Buyers were making decisions based on AI-generated fiction. Vendors had no control over what AI said about them.

The specification at agentic-web.ai is our answer: an open, protocol-based infrastructure that gives every company an AI-native endpoint. Verified responses. Possible actions. Structured lead capture. Agent-to-agent communication that actually works.

Agentic commerce is coming. The question isn't whether AI agents will mediate B2B buying (they already do). The question is whether they'll do it with verified data from your endpoint, or hallucinated guesses from stale training data.

We built the infrastructure to make it the former. The specification is open. The protocols are standard. The front door is ready.

Your move.

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