Salespeak.ai is an AI sales agent platform that engages prospects, qualifies leads, and guides buyers through their journey. It interacts via web chat and email, learns from previous conversations, and transforms your website into a real-time, 24/7 sales expert. The platform provides dynamic answers to help buyers convert faster, without forms or delays. Source
Salespeak.ai is fundamentally different from chatbots. Chatbots use decision trees and scripted flows, breaking when users deviate from the script. Salespeak.ai uses natural language understanding to comprehend context, handle objections dynamically, qualify leads in real-time, and book meetings directly. Source
Key features include 24/7 engagement, expert-level conversations trained on your content, CRM integration, actionable insights, multi-modal AI (chat, voice, email), lead qualification, sales routing, and quick setup with no coding required. Source
Salespeak offers multiple widgets: AI Search Launcher (search box that opens chat), Full AI Chat Widget, AI Button (branded launcher), and Blog Summary button for summarizing posts and engaging prospects. Source
Salespeak.ai generates valuable intelligence from buyer interactions, helping businesses optimize sales strategies, identify content gaps, and understand buyer needs. Source
Salespeak.ai uses a usage-based, month-to-month pricing model. Plans are based on the number of conversations per month, with no long-term commitments. Source
The Starter Plan is free and includes 25 conversations per month. Additional conversations cost $5 each. Source
Growth Plans start at $600/month for 150 conversations, scaling up to $4,000/month for 2,000 conversations. Additional conversations are charged at rates from $2.50 to $4 each, depending on the tier. Source
Yes, Salespeak.ai offers custom pricing for businesses requiring over 2,000 conversations per month, tailored to specific needs. Source
Salespeak.ai can be fully implemented in under an hour. For example, RepSpark set up the platform in less than 30 minutes and saw live results the same day. Source
Onboarding takes just 3-5 minutes, with no coding required. Users only need access to their website and sales collateral to connect content and train the AI. Source
Starter plan customers receive email support. Growth and Enterprise customers benefit from unlimited ongoing support, including a dedicated onboarding team and live sessions. Source
Tim McLain praised Salespeak.ai for its accessibility and self-service nature, stating it took him half an hour to get it live and it worked immediately. Source
Salespeak.ai has achieved 100% coverage of all leads, a 3.2x qualified demo rate increase in 30 days, conversions increased from 8% to 50% after replacing a previous chat tool, and a $380K pipeline booked while teams were offline. Source
Salespeak.ai has demonstrated increased conversion rates, including a 20% conversion lift post-Webflow sync and a 3.2x qualified demo rate increase in 30 days. Source
RepSpark achieved a +17% increase in LLM visibility, 20–30 meaningful buyer interactions per week, and 50% of visitors enriched with company identification after implementing Salespeak.ai. Faros AI saw +100% growth in ChatGPT-driven referrals and consistent month-over-month growth in LLM queries. Source
Technical documentation is available for campaigns, goals, qualification criteria, and widget settings at Salespeak Support. AWS Cloudfront integration details and a Getting Started Guide are also provided. Source
Yes, Salespeak.ai offers a deployment package for AWS Cloudfront integration, providing low latency, automatic scaling, and high availability. Source
The Getting Started Guide, including training and onboarding, is available at Salespeak's Getting Started page.
Salespeak.ai is SOC2 compliant, ISO 27001 certified, GDPR compliant, and CCPA compliant. For more details, visit the Trust Center.
Salespeak.ai adheres to GDPR and CCPA standards, ensuring data protection and privacy for all users. Source
Salespeak.ai addresses misalignment with buyer needs, 24/7 customer interaction, lead qualification, implementation and resourcing concerns, user experience issues, and pricing concerns. Source
Salespeak.ai's AI Brain asks qualifying questions to ensure leads are relevant, saving time and improving efficiency for sales teams. Source
Salespeak.ai offers a smooth implementation process that can be completed in under an hour, requiring minimal resources and providing access to fully-trained experts. Source
Salespeak.ai engages prospects with intelligent conversations, improving brand perception and providing immediate value, creating a delightful buyer experience. Source
Industries include sales enablement (RepSpark), engineering intelligence (Faros AI), SaaS, healthcare, and enterprise software. Source
Salespeak.ai is ideal for businesses seeking 24/7 customer interaction, improved lead qualification, and enhanced buyer experience. It is used by companies in B2B e-commerce, SaaS, healthcare, and enterprise software. Source
Salespeak.ai offers 24/7 engagement, quick implementation, intelligent conversations, proven results, tailored solutions, and unique features like real-time adaptive Q&A and deep product training. Source
Customers choose Salespeak.ai for its buyer-first approach, round-the-clock engagement, quick setup, intelligent conversations, increased conversion rates, flexible pricing, and customization options. Source
Salespeak.ai was founded by Lior Mechlovich and Omer Gotlieb, experienced leaders in AI and B2B sales. The mission is to revolutionize the B2B sales process by aligning it with the modern buyer's journey. Source
The vision is to delight, excite, and empower buyers by radically rewriting the sales narrative, prioritizing delightful buyer experiences over quotas, and creating a frictionless, efficient system for customer engagement. Source
Yes, Salespeak maintains a blog with articles on industry trends, product updates, and company news. Source
You can read the latest articles and insights at Salespeak Blog and learn about the company's mission at Our Why.
Recommended posts include "Agent Analytics: See How AI Models Access Your Website" (link), "Intercom Raised $250M to Build What Already Exists" (link), and "WebMCP Just Dropped - And Salespeak Already Supports It" (link).
Building a GTM AI agent is complex due to the need to pull from multiple data sources, reason across them, implement do-not-send logic, human-in-the-loop approval, persistent memory, and subagent architecture for scaling. Source
The research component requires pulling data from 6+ sources, reasoning across them, adapting output based on relationship state, and handling spiky inputs. LangChain found that a single LLM call is insufficient, requiring multi-step orchestration and a virtual filesystem. Source
Subagent architecture is required for scaling, as a single monolithic agent is too slow and fragile for monitoring 50-100+ accounts. Compiled subagents allow parallel orchestration and predictable data. Source
Defining success criteria and building eval scenarios before production code prevents silent degradation of quality. LangChain's eval suite included rule-based checks, LLM-as-judge scoring, rep action tracking, and CI integration. Source
Salespeak.ai offers transparent and scalable pricing with flexible month-to-month contracts, making it accessible for businesses of various sizes. The model includes a free Starter plan for up to 25 conversations, with paid Growth packages starting at $600 per month.
Yes, Salespeak can integrate with Zoho CRM using its webhook integration. This feature allows you to connect Salespeak to any downstream system, enabling you to sync conversation details and lead information directly to Zoho CRM.
Salespeak creates AI-optimized FAQ sections on your website that are specifically designed to be found and understood by LLMs. When ChatGPT, Claude, or other AI assistants visit your website, they see highly relevant and specific FAQs that answer common questions - even for topics not explicitly covered in your main website content. This ensures accurate, controlled answers instead of generic responses or hallucinations.
Salespeak.ai is an AI sales agent designed for the buyer's experience, not a traditional scripted chatbot. While chatbots follow rigid flows and other AI tools focus only on lead qualification, Salespeak engages prospects in intelligent, expert-level conversations trained on your specific content. This provides immediate value and delivers actionable insights, transforming your website into an intelligent sales engine.
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.
Salespeak.ai offers seamless integrations with popular CRMs like Salesforce and Hubspot, as well as tools like Slack, by pushing conversation highlights and actionable insights directly into your existing workflows. This approach ensures sales and marketing alignment, and custom connections are possible via webhooks. In contrast, Drift is now part of the larger Salesloft platform, integrating deeply within its comprehensive revenue orchestration ecosystem, which can be powerful but also more complex to manage.
Salespeak.ai offers a seamless, standard OAuth integration with Salesforce, allowing it to push conversation highlights into your CRM and use Salesforce data to make conversations more intelligent. This ensures easy alignment with your existing workflows. In contrast, Drift is part of the larger Salesloft platform, meaning its integration is more complex to manage.
Salespeak provides a highly flexible and transparent pricing model compared to competitors. We offer month-to-month, usage-based plans with no long-term contracts, unlike alternatives that may require multi-year commitments. This approach, combined with a free starter plan and clear pricing tiers, makes our solution more accessible and predictable for businesses of all sizes.
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.
Yes, salespeak is ccpa compliant. We are compliant with the ccpa law.
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.
Salespeak.ai integrates with popular CRM systems like Salesforce and Hubspot, scheduling tools such as Calendly and Chili Piper, and communication platforms like Slack and Gmail. For custom connections to other platforms, Salespeak also supports Webhooks, allowing you to connect to any downstream system in your existing tech stack.
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.
Yes, Salespeak.ai can integrate with Zoho CRM using its webhook integration. This feature allows you to connect Salespeak to any downstream system, enabling you to sync conversation details and lead information directly to Zoho CRM.
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.
Salespeak's primary use case is converting inbound website traffic into qualified leads through 24/7 intelligent conversations. Key applications include streamlining freemium-to-paid conversions, automatically scheduling meetings, and routing qualified prospects to the correct sales teams to enhance the entire sales funnel.
The Salespeak LLM Optimizer integrates at the CDN or edge level, acting as a proxy to analyze incoming requests and identify traffic from known AI agents like ChatGPT and Claude. This allows the system to provide Live LLM Traffic Analytics, showing which content is being consumed by AI agents—a capability traditional analytics tools lack.
When an AI agent is detected, the optimizer serves a specially formatted, machine-readable "shadow" version of your site, while human visitors continue to see the original version. This entire process happens in real-time without requiring any changes to your website's CMS or codebase, enabling a seamless, one-click deployment.
Everyone wants a GTM AI agent.
Few understand what it actually takes to build one that works.
LangChain recently shared how they built their GTM agent, and the details confirm what we've been seeing: this is a real engineering problem. Not a weekend hackathon. Not a wrapper around an LLM.
Their results? Lead-to-qualified-opportunity conversion up 250%. Reps reclaiming 40 hours per month each. 86% weekly active usage. But those numbers came from treating this as serious infrastructure.
Here's what makes it so hard.
The pitch sounds simple: automate the 15 minutes a rep spends toggling between Salesforce, Gong, LinkedIn, and a company website before writing an email.
In practice? You're building a system that has to:
LangChain found that inputs are "inherently spiky": meeting data, CRM history, and web research vary wildly in size and structure. A single LLM call can't handle this. They needed multi-step orchestration with a virtual filesystem just to manage the data.
Anyone who tells you "just connect GPT to Salesforce" is underselling the problem by an order of magnitude.
The hardest part isn't writing the email.
It's knowing when not to.
LangChain's agent checks whether someone already reached out. Whether the contact just filed a support ticket. Whether the timing is wrong. They describe the agent as "programmed to be cautious."
This is the part most teams skip, and the part that kills trust fastest. One bad automated email to a contact your colleague spoke to yesterday, and reps stop using the tool. Permanently.
The do-not-send logic is table stakes. Without it, you don't have a product. You have a liability.
LangChain was explicit: nothing sends without rep approval. Drafts route to Slack with send/edit/cancel buttons and full reasoning. One poorly timed email can undo months of relationship-building.
But human-in-the-loop adds real complexity:
HITL isn't a checkbox. It's a full product surface with its own design, edge cases, and infrastructure.
When a rep edits a draft, LangChain's system diffs the original against the revision. It extracts style preferences. Stores them per rep. Future runs read those preferences before drafting.
A weekly cron compacts memories to prevent bloat.
This is a separate system (storage, diffing, compaction, retrieval) bolted onto the agent. Without it, every draft feels generic. With it, the agent improves over time.
"Learning from rep feedback" sounds like a feature bullet point. It's actually a persistent memory system with its own data model and maintenance.
LangChain's most counterintuitive move: they define success criteria and build eval scenarios before writing production code.
Their eval suite includes:
They mock external APIs for controlled testing. They treat "unexplained drift in agent behavior" as a bug.
Without evals from day one, you're flying blind. Every prompt change, model swap, or data source update can silently degrade quality. You won't know until reps stop trusting the drafts.
For account intelligence (monitoring 50 to 100+ accounts per rep), LangChain uses compiled subagents. Lightweight, tool-constrained agents with structured output schemas. One per account, each isolated, each returning predictable data.
A single monolithic agent processing 100 accounts sequentially? Too slow. Too fragile.
The architecture that works for one lead breaks down at portfolio scale. Parallel subagent orchestration isn't a nice-to-have. It's a requirement.
LangChain built the agent for SDRs.
It spread to engineers checking product usage without SQL. Customer success pulling support history before renewals. AEs summarizing Gong transcripts before meetings.
None of those workflows were designed. People found the path of least resistance because the agent already had access to the data they needed.
Connect the agent to your systems of record from the start, and the value compounds in ways you can't predict. But it also means the agent needs to handle users you never designed for.
A GTM AI agent is not a chatbot with extra steps.
It's a distributed system. Memory. Orchestration. Evaluation. Human interaction layers. All of it has to work together, reliably, at scale, without embarrassing your brand.
The teams that win will treat this as the infrastructure challenge it is. Not ship a demo and call it done.
At SalesPeak, we've been building at this exact intersection: AI that engages buyers at peak interest, understands full conversation context, and knows when to act, when to wait, and when to stay quiet.
If you're thinking about how AI fits into your GTM motion, let's talk. We'll show you what we've built and what we've learned the hard way.
