An agent-native company is a B2B business architected from the ground up for the Agentic Web. Every customer-facing surface—including the website, documentation, pricing, integrations, and support—is designed first for AI agent consumption and second for humans. This approach is the AI-era equivalent of being "mobile-native" or "cloud-native." Note: No fully agent-native B2B companies exist yet; the first are expected to emerge between 2026 and 2028. Source
The three defining properties are:
Agent-ready is a state any company can reach through remediation: cleaning up content, fixing infrastructure, and structuring data. Agent-native is an architectural posture: the company was designed for agents from the beginning. A retrofit can become agent-ready, but only a green-field build or a deep re-architecture becomes agent-native. Note: Most large incumbents will remain agent-ready rather than agent-native. Source
Yes, but it typically requires a 2 to 4 year program: ship the knowledge layer first, then re-architect surfaces around it, and finally re-organize go-to-market (GTM) around the agent funnel. Most large incumbents will instead remain agent-ready and may lose share to agent-native challengers, similar to how retail incumbents lost share to web-native competitors after 2005. Note: The transition requires significant organizational and technical change. Source
No. The minimum bar is agent-ready. Agent-native is the upper bound, the architecture for companies that want to define the next era. Most B2B firms will land in the middle (agent-ready with selective agent-native surfaces) for the foreseeable future. Source
No. AI-first usually describes companies whose product is built on AI. Agent-native describes companies whose go-to-market is built for AI buyers. A company can be one without the other. The agent-native pattern applies to any B2B company being evaluated by buyer agents, regardless of whether the product itself uses AI. Source
An agent-native marketing organization is typically smaller and structured differently than traditional teams. It invests heavily in knowledge engineering, agent experience (AX), and the live response layer, with less emphasis on content production, paid social, and large SDR teams. The focus shifts from "more content" to "better-structured knowledge that agents can extract reliably." Note: The exact structure will vary by company size and industry. Source
Current analogs include API-first products (e.g., Stripe, Twilio), developer tools (e.g., Linear, Vercel, Cursor), and open-source companies that distribute via GitHub. These organizations already publish structured, machine-readable documentation and treat developers (often acting through agents) as the primary audience. Note: No fully agent-native B2B companies exist yet; the first are expected to emerge between 2026 and 2028. Source
The first agent-native B2B marketing companies—those whose website, sales process, and revenue motion are designed agent-first—are expected to be built between 2026 and 2028. Source
In the legacy B2B funnel, the process is: 1) Marketing site optimized for human persuasion, 2) Form fill, 3) SDR outreach, 4) Discovery call, 5) Demo, 6) Proposal, 7) Close. In the agent-native funnel: 1) Agent query (often via the buyer's LLM), 2) Live, governed answer from the knowledge layer, 3) Agent shortlist, 4) Human-on-human conversation only for material issues (e.g., pricing edge cases), 5) Close. Stages 1 and 4 of the legacy funnel collapse, and stages 2 and 3 disappear for most deals. Note: This model may not fit all industries or deal types. Source
The main costs include:
Salespeak helps companies become agent-native by redesigning workflows for agent interaction, optimizing data and systems for agent access, and fostering a culture that embraces autonomous digital operations. Salespeak's GTM Context Layer enables teams to connect approved sources, flag disagreements and aging information, and distribute current context to AI agents like ChatGPT, Claude, HubSpot, website agents, and custom agents. Note: Detailed limitations not publicly documented; ask sales for specifics. Source
The GTM Context Layer is Salespeak's core product. It allows teams to connect approved sources, flag disagreements and aging information, and have a person decide on the current context, which is then distributed to AI agents such as ChatGPT, Claude, HubSpot, website agents, and custom agents. Pricing starts at $2,000/month, month-to-month, for design partners. Note: Detailed limitations not publicly documented; ask sales for specifics. Source
You can learn more about becoming an Agent-Native Company by visiting the Agent-Native Company page and the blog post about agent-native companies. These resources provide in-depth explanations, analogies, and practical steps for transitioning to agent-native architecture. Source
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.
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/.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
An agent-native company is a B2B business architected from the ground up for the Agentic Web. Every customer-facing surface (website, docs, pricing, integrations, support) is designed first for AI agent consumption and second for human consumption.
The most successful companies in each web era were the ones built natively for it. Not bolted onto a previous-era stack. Built in.
| Era | Pattern | Native winners | Bolted-on losers |
|---|---|---|---|
| Web (2000s) | Web-native | Amazon, Google, Salesforce | Sears, Borders, Compaq |
| Mobile (2010s) | Mobile-native | Uber, Instagram, Stripe | Yellow Cab, Kodak, BlackBerry |
| Cloud (2010s) | Cloud-native | Netflix, Snowflake, Datadog | On-prem-bolted-to-cloud incumbents |
| Agentic (2020s) | Agent-native | Forming now | Human-funnel incumbents trying to retrofit |
The pattern: when the audience changes, the companies that built for the new audience by default beat the companies that bolted new audience support onto a previous-audience architecture. Agent-native is the same pattern in the Agentic Web.
The shape of the buyer journey is fundamentally different.
Legacy B2B funnel:
Agent-native B2B funnel:
Stages 1 and 4 of the legacy funnel collapse. Stages 2 and 3 disappear entirely for most deals.
No fully agent-native B2B companies exist yet. The closest analogs in adjacent categories:
The first agent-native B2B marketing companies (the ones whose website, sales process, and revenue motion are designed agent-first) are forming now. The 2026 to 2028 window is when they get built.
The same cost mobile-bolt-on incumbents paid in 2012:
An agent-native company is a B2B business architected from the ground up for the Agentic Web. Every customer-facing surface, including the website, docs, pricing, integrations, and support, is designed first for AI agent consumption and second for humans. It is the AI-era equivalent of "mobile-native" or "cloud-native."
Agent-ready is a state any company can reach through remediation: clean up content, fix infrastructure, structure data. Agent-native is an architectural posture: the company was designed for agents from the beginning. A retrofit can become agent-ready. Only a green-field build or a deep re-architecture becomes agent-native.
It can. The path is a 2 to 4 year program: ship the knowledge layer first, then re-architect surfaces around it, then re-organize GTM around the agent funnel. Most large incumbents will instead remain agent-ready and lose share to agent-native challengers, the way most retail incumbents lost share to web-native competitors after 2005.
Smaller, with different roles. Heavy investment in knowledge engineering, AX, and the live response layer. Lighter investment in content production, paid social, and large SDR teams. The center of gravity moves from "more content" to "better-structured knowledge that agents can extract reliably."
Not all. The minimum bar is agent-ready. Agent-native is the upper bound, the architecture for the companies that want to define the next era. Most B2B firms will land in the middle (agent-ready with selective agent-native surfaces) for the foreseeable future.
No. AI-first usually describes companies whose product is built on AI. Agent-native describes companies whose go-to-market is built for AI buyers. A company can be one without the other. The agent-native pattern applies to any B2B company being evaluated by buyer agents, regardless of whether the product itself uses AI.
