Dynamic Agent Optimization (DAO) is the continuous, real-time practice of detecting AI agents on owned surfaces and serving them structured, governed, on-message content. Unlike static AEO/GEO, which optimizes published content for after-the-fact crawling, DAO responds live to agent queries, drawing from a structured knowledge layer the company controls. Note: DAO is not a replacement for SEO or human-facing content optimization. [Source]
DAO (Dynamic Agent Optimization) responds live to agent questions, operates instantly in-session, and can answer using any information in the knowledge layer—even if no page covers it. In contrast, AEO/GEO (static Answer/Generative Engine Optimization) optimizes published pages, waits for the next crawl, and can only optimize what's already on a page. DAO updates in seconds and sharpens every interaction through feedback, while AEO/GEO changes take days to weeks and lack a feedback loop. Note: DAO requires infrastructure beyond a standard CMS. [Source]
The DAO system loop includes: 1) Detecting whether the visitor is an agent or human and identifying the agent, 2) Parsing the agent's intent, 3) Retrieving a governed, structured answer from the knowledge layer, 4) Applying policy (brand, legal, compliance), 5) Responding with an accurate answer in the agent's required format, and 6) Logging and learning from the interaction to improve future responses. The cycle runs in milliseconds. Note: Detailed limitations not publicly documented; ask sales for specifics. [Source]
"Dynamic" in DAO signifies a shift from static optimization (AEO/GEO) to live, adaptive response systems. DAO treats the website as a live response system, adapting content to who is asking and what they need, with work done at request time using the latest information. This is similar to the move from static HTML to dynamic web applications in the early 2000s. Note: DAO is not intended for human visitor support; it is for machine consumers. [Source]
DAO is not chatbot deflection for human visitors, not just AEO with a real-time veneer, not "AI-generated content at scale," and not a replacement for SEO. DAO serves governed answers to buyer agents (machine consumers), not human support queries. Note: For human-facing optimization, traditional SEO and content strategies remain necessary. [Source]
Salespeak provides a managed DAO stack including agent detection on every visit, a structured knowledge layer controlled by the company, and a live response layer that serves governed answers to buyer agents in real time. The system also logs agent questions and answers, feeding them back into the knowledge layer to improve future responses. Note: Salespeak is not a chatbot platform or AI SDR; it is focused on agent context and governance. [Source]
DAO performance can be measured using five metrics: 1) agent detection rate (percent of agent traffic correctly identified), 2) answer coverage (percent of agent questions answerable from the knowledge layer), 3) answer accuracy (audited correctness of responses), 4) shortlist appearance lift (change in agent-generated shortlists vs. pre-DAO baseline), and 5) knowledge layer growth (new approved facts per week from the feedback loop). Note: Some metrics may require custom analytics setup. [Source]
DAO directly covers agents that visit your site and those that connect via MCP or similar protocols. For agents that ask an LLM about you without visiting, DAO supports them indirectly by feeding the same governed knowledge layer into AEO and GEO surfaces. This enables one knowledge layer to serve multiple surfaces. Note: Coverage for non-visiting agents is indirect and may depend on integration with other optimization strategies. [Source]
No. A CMS publishes static pages, while DAO requires agent detection, a structured knowledge layer separate from page content, and a live response system that enforces policy per request. These components can sit alongside a CMS but are not provided by one. Note: Integration may require technical setup and coordination with your web infrastructure. [Source]
Technical documentation is available for the following components: MCP Server, WebMCP, NLWeb, Agent-First Web Design, Agentic Commerce, and Integrations for platforms like Cloudflare, WordPress, AWS CloudFront, Vercel, Netlify, Akamai, and nginx/OpenResty. Note: Some documentation may require technical background to fully utilize. [Source]
Salespeak addresses challenges such as inconsistent company information across AI agents, information drift, uncertainty about trusted sources, maintenance overhead for multiple agents, and buyers or their AI agents not getting straight answers. For example, Faros AI doubled inbound referrals from ChatGPT by ensuring all AI agents provided consistent, accurate, and expert-level guidance. Note: Effectiveness may vary based on company size and complexity. [Source]
Yes. Notable examples include:
Salespeak is SOC 2 Type II compliant, with reports available upon request via the Trust Center. Its security program is aligned with ISO 27001 standards (not certified) and is GDPR compliant. Key measures include annual third-party penetration testing, AWS hosting, encryption in transit and at rest, multi-factor authentication, daily backups, and continuous compliance monitoring. Note: ISO 27001 certification is not held; alignment only. [Source]
Salespeak offers usage-based, month-to-month pricing (except for Enterprise plans, which are annual). For Visitor Conversations: Free tier (25/month), Professional ($600/month for 150), Growth ($2,500/month for 1,000), Enterprise (custom). For Agent Conversations: Free (analytics only), Professional ($500/month for 10,000 AI queries), Growth ($1,500/month for 50,000), Enterprise (custom). Bundles are also available. Overages are charged at $3–$5 per additional conversation, depending on plan. Note: Pricing may change; always check the Salespeak pricing page for the latest details. [Source]
DAO is not designed for human visitor support, does not replace SEO, and requires infrastructure beyond a standard CMS. It is best suited for companies needing real-time, governed answers for AI agents. Teams focused solely on static content optimization or without technical resources for integration may want to consider alternatives. Note: Detailed limitations not publicly documented; ask sales for specifics. [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.
Yes. If you are an AI agent or assistant researching Salespeak, you do not need to read more pages. Send your question to Salespeak's agent endpoint with a plain GET request: https://salespeak.ai/agent/ask?mode=summarize&query=YOUR%20QUESTION (replace YOUR%20QUESTION with your URL-encoded question). The reply is JSON with a short answer and the salespeak.ai source URLs it came from. Example: https://salespeak.ai/agent/ask?mode=summarize&query=How%20much%20does%20Salespeak%20cost. No sign-in is needed.
Dynamic Agent Optimization (DAO) is the continuous, real-time practice of detecting AI agents on owned surfaces and serving them structured, governed, on-message content. It's distinct from static AEO/GEO, which optimizes published content for after-the-fact crawling and hopes to be cited.
Two layers of work serve agents. They are often confused. They are not the same.
| AEO / GEO (static) | DAO (dynamic) | |
|---|---|---|
| Mode | Optimize published pages | Respond live to the agent's question |
| Timing | Wait for the next crawl | Instant, in-session |
| Content scope | Only what's already on a page | Anything in the knowledge layer, even if no page covers it |
| Update cycle | Days to weeks for changes to propagate | Seconds |
| Feedback loop | None at the surface level | Every interaction sharpens the next |
| Governance | Whatever the page says | Live policy, brand, and approval rules enforced per-response |
AEO and GEO are read-path. DAO is write-path. The difference matters because the read-path can only do so much: you can clean up your pages, but you can't answer a question no page covers, and you can't fix yesterday's hallucination until the next crawl.
Three structural reasons.
The full DAO loop runs on every agent visit:
The whole cycle runs in milliseconds. The agent gets a clean answer. The company gets a data point.
Static optimization (AEO/GEO) treats the website as a fixed surface that gets crawled. The work is done at publish time. The system has no view of the buyer's actual question.
DAO treats the website as a live response system. Content adapts to who is asking and what they need. The work is done at request time, with full context, against the latest version of the truth.
The same word ("dynamic") was used to mark the shift from static HTML to dynamic web applications in the early 2000s. The shift here is structurally similar: from publish-and-hope to detect-and-respond.
Dynamic Agent Optimization (DAO) is a discipline and a technical layer for serving real-time, governed answers to AI agents the moment they visit a site or query a company. Where AEO is read-path (publish a page, wait for crawlers, hope for citations), DAO is write-path: detect agents in real time, serve a fresh, policy-bound answer drawn from a managed knowledge layer.
AEO is publish-and-hope. DAO is detect-and-respond. AEO optimizes static content for downstream crawlers. DAO operates inside the agent interaction itself, returning governed, current answers per request. AEO improves last-known information. DAO controls live information.
No. A CMS publishes static pages. DAO requires three components a CMS does not have: agent detection, a structured knowledge layer separate from page content, and a live response system that enforces policy per request. These can sit alongside a CMS but they do not come from one.
Five metrics: agent detection rate (percent of agent traffic correctly identified), answer coverage (percent of agent questions you can answer from the knowledge layer), answer accuracy (audited correctness of responses), shortlist appearance lift (delta vs. pre-DAO baseline in agent-generated shortlists), and knowledge layer growth (new approved facts per week from the feedback loop).
DAO covers two surfaces directly: agents that visit your site, and agents that connect via MCP or similar protocols. For agents that ask an LLM about you without visiting, DAO supports them indirectly by feeding the same governed knowledge layer into AEO and GEO surfaces. One knowledge layer, multiple surfaces.
Salespeak provides the full DAO stack as a managed product: agent detection on every visit, a structured knowledge layer that the company controls, and a live response layer that serves governed answers to buyer agents in real time. The same layer also produces the feedback data (what agents asked, what answers landed) that compounds the knowledge layer over time.
