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54 Listings in Sales AI Agents Available
What is Salesloft? Salesloft is a predictive revenue system for B2B sales teams that combines sales engagement, conversation intelligence, deal management and forecasting with AI agents. After combining with Clari, its portfolio includes Clari Forecast. Key capabilities of Salesloft Cadence: Sales engagement and outreach sequences. Conversation Intelligence: Buyer and seller call insights. Deals: Opportunity management. Clari Forecast: Sales forecasting. Inspect: Pipeline visibility. How Salesloft works Salesloft AI agents interpret data, prioritize signals, trigger automated actions and push next steps to revenue teams, working alongside human sellers to run deal plays and prepare meetings. Cadence and Rhythm drive outreach while Inspect and forecasting give managers pipeline visibility. Who uses Salesloft? B2B revenue teams including sellers, managers and revenue leaders use Salesloft; the vendor cites 4,000+ sales teams. Salesloft pricing Salesloft does not publish pricing and directs visitors to talk to sales for a quote. Salesloft alternatives People.ai captures revenue activity data, Regie.ai generates sales content, and Qualified focuses on conversational pipeline. Salesloft is distinguished by uniting engagement, conversation intelligence and forecasting.
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What is Momentum? Momentum is an AI revenue orchestration platform that captures data from customer conversations and automates work across revenue systems. Salesforce signed an agreement to acquire Momentum on February 18, 2026, and completed the deal on March 2, 2026. Key capabilities of Momentum Deal Execution Agent: post-call tasks such as Salesforce field updates and notes Customer Retention Agent: flags churn risk and sentiment AI CRO Agent: executive insight on accounts, reps and pipeline Coaching Agent: data-driven coaching from call analysis MEDDIC Autopilot: keeps qualification data clean Slack deal rooms: smart notifications and automation in Slack How Momentum works Momentum ingests voice and video calls from platforms such as Zoom and Google Meet and converts the unstructured conversation into structured data. Agents then update CRM fields, write summaries, and post alerts to Slack. Salesforce says the ingestion engine will extend Agentforce 360 and Slackbot. Who uses Momentum? Revenue teams, sales leaders and customer success teams use it. The vendor lists customers including Ramp, 1Password, Demandbase, Owner and Jasper, and users report time saved on data entry and better CRM accuracy. Momentum pricing Momentum does not publish pricing on its site, and plans are quoted by the vendor. Because of the Salesforce acquisition, packaging may change, so contact Momentum or Salesforce for current terms. Momentum alternatives Alternatives include Gong for conversation intelligence, Salesforce Agentforce for native CRM agents, Outreach for sales engagement, Clay for data enrichment, and Apollo.io for prospecting.
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Saaskart Market Grid™
Explore how leading Sales AI Agents solutions compare based on customer satisfaction, market presence, adoption, and buyer feedback. The Market Grid helps you identify category leaders, high-performing solutions, and emerging products within the Sales AI Agents ecosystem.
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See where sales ai agents fits in a complete stack, with the other software, AI agents and services each business needs.
What is Conversica? Conversica is a revenue assistants AI agent offering AI revenue assistants that engage, qualify and follow up with leads over email and chat. Founded in 2007 and based in Foster City, California, USA, Conversica helps B2B marketers and auto dealers automate AI revenue assistants work and get results faster. Key capabilities of Conversica Lead follow-up Two-way AI email Lead qualification Dealer and B2B playbooks Dealer workflow integration Automated reports How Conversica works Conversica takes text and email as input and produces email and text. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as CDK Global, Reynolds and Reynolds, DealerSocket and Salesforce, so the agent works inside existing workflows. Who uses Conversica? Conversica is built for B2B marketers and auto dealers. It suits teams that want lead follow-up and two-way AI email without adding headcount, while keeping people in control of review and final decisions. Conversica vs Drift Conversica is often compared with Drift. Conversica stands out for lead follow-up and lead qualification. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Humantic AI? Humantic AI is a buyer intelligence AI agent offering buyer personality insights that tell reps how to communicate with each prospect. Founded in 2018 and based in San Francisco, California, USA, Humantic AI helps sales and recruiting teams automate buyer intelligence work and get results faster. Key capabilities of Humantic AI Buyer personality profiles Communication guidance Email personalization Deal team insights CRM integration Analytics and reporting How Humantic AI works Humantic AI takes text and profile data as input and produces text and insights. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Salesforce, HubSpot, LinkedIn and Gmail, so the agent works inside existing workflows. Who uses Humantic AI? Humantic AI is built for sales and recruiting teams. It suits teams that want buyer personality profiles and communication guidance without adding headcount, while keeping people in control of review and final decisions. Humantic AI vs Crystal Humantic AI is often compared with Crystal. Humantic AI stands out for buyer personality profiles and email personalization. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is 11x? 11x is a digital sales workers AI agent offering digital AI workers for revenue teams, including Alice the AI SDR and Julian the phone agent. Founded in 2022 and based in San Francisco, California, USA, 11x helps B2B revenue teams automate digital sales workers work and get results faster. Key capabilities of 11x AI SDR Alice AI phone agent Julian Multichannel outreach Lead research CRM sync Deal insights How 11x works 11x takes text and CRM data as input and produces email and audio. It is powered by Multiple LLMs (managed) models, with the vendor managing prompts, models and updates. It connects to tools such as Salesforce, HubSpot, LinkedIn and Gmail, so the agent works inside existing workflows. Who uses 11x? 11x is built for B2B revenue teams. It suits teams that want AI SDR Alice and AI phone agent Julian without adding headcount, while keeping people in control of review and final decisions. 11x vs Artisan 11x is often compared with Artisan. 11x stands out for AI SDR Alice and multichannel outreach. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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What is Bounti? Bounti is a sales research AI agent offering an AI sales assistant that researches accounts and generates briefs, talk tracks and outreach. Bounti helps B2B sales teams automate sales research work and get results faster. Key capabilities of Bounti Account research Meeting prep briefs Persona insights Outreach drafts Account briefs Personalized outreach drafts How Bounti works Bounti takes text and web as input and produces text and reports. It combines large language models with task-specific AI, with the vendor managing prompts, models and updates. It connects to tools such as Salesforce, HubSpot, Gmail and Google Calendar, so the agent works inside existing workflows. Who uses Bounti? Bounti is built for B2B sales teams. It suits teams that want account research and meeting prep briefs without adding headcount, while keeping people in control of review and final decisions. Bounti vs Clay Bounti is often compared with Clay. Bounti stands out for account research and persona insights. The right choice depends on your workflow, integrations and budget, so compare both on a real task.
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Sales AI agents automate and assist selling, from prospecting and outreach to deal intelligence and forecasting, so reps spend more time with buyers and less on busywork. This guide explains what sales AI is, how it works, what matters, and how to choose a platform.
Sales AI agents automate and assist selling, from prospecting and outreach to deal intelligence and forecasting, so reps spend more time with buyers and less on busywork. This guide explains what sales AI is, how it works, what matters, and how to choose a platform.
Sales AI applies machine learning and generative models across the sales cycle: finding and prioritizing prospects, drafting and personalizing outreach, capturing and analyzing conversations, scoring leads and deals, and forecasting revenue.
It appears both as standalone tools (AI SDR/prospecting agents, conversation intelligence, forecasting) and as AI features inside CRMs and sales-engagement platforms.
The category is shifting from point assistants toward agentic selling, systems that research accounts, draft and send sequenced outreach, log activity, and surface next-best-actions with human oversight. Buyers weigh pipeline impact, data quality, deliverability, and CRM fit.
Sales AI ingests CRM, conversation, and intent data, then prospects and prioritizes accounts, generates personalized outreach, captures and analyzes calls and emails, scores leads and deals, and recommends next steps, surfacing actions or executing within set rules.
Platforms combine data enrichment, generative outreach, conversation intelligence, and predictive scoring/forecasting, integrated with the CRM, email, and dialer so activity is captured and acted on automatically.
Sales teams connect data and define ICP, sequences, and guardrails; reps review AI recommendations and drafts, while managers use deal and forecast intelligence to coach and plan.
Find and enrich target accounts and contacts and prioritize them by fit and intent signals.
Generate tailored emails and sequences at scale using account research and CRM context.
Record, transcribe, and analyze calls for talk ratios, topics, risks, and coaching insights.
Predict which leads and deals are most likely to convert so reps focus where it pays off.
Surface deal risk and forecast revenue from real activity and engagement signals.
Auto-log activity, update records, and recommend next-best-actions to keep the CRM accurate.
Automating research, outreach drafting, and CRM data entry frees reps to focus on buyers.
Scoring and intent signals focus effort on the accounts and deals most likely to close.
Generate relevant, tailored outreach without hours of manual research per prospect.
Conversation intelligence reveals what top reps do so managers can coach the rest.
Activity-based signals improve pipeline visibility and forecast reliability.
| Type | Best for | Ideal size | Pros | Limitations |
|---|---|---|---|---|
| AI SDR / prospecting agents | Automated research and outreach | SMB to enterprise | Scales pipeline generation | Deliverability and quality oversight needed |
| Conversation intelligence | Call recording, analysis, coaching | Any | Coaching and deal insight | Consent-sensitive |
| Predictive scoring & forecasting | Lead/deal scoring, revenue forecast | Mid-market to enterprise | Focus and visibility | Needs clean historical data |
| Sales-engagement AI | Sequenced outreach and automation | Any | Efficiency across the funnel | Risk of generic spam without controls |
Technology: Technology sales teams use AI to prioritize accounts, personalize outreach at scale, capture and coach on conversations, and forecast revenue more accurately, while keeping reps in control of relationships.
Healthcare: Healthcare sales teams use AI to prioritize accounts, personalize outreach at scale, capture and coach on conversations, and forecast revenue more accurately, while keeping reps in control of relationships.
Financial Services: Financial Services sales teams use AI to prioritize accounts, personalize outreach at scale, capture and coach on conversations, and forecast revenue more accurately, while keeping reps in control of relationships.
Retail & E-commerce: Retail & E-commerce sales teams use AI to prioritize accounts, personalize outreach at scale, capture and coach on conversations, and forecast revenue more accurately, while keeping reps in control of relationships.
Education: Education sales teams use AI to prioritize accounts, personalize outreach at scale, capture and coach on conversations, and forecast revenue more accurately, while keeping reps in control of relationships.
Professional Services: Professional Services sales teams use AI to prioritize accounts, personalize outreach at scale, capture and coach on conversations, and forecast revenue more accurately, while keeping reps in control of relationships.
Manufacturing: Manufacturing sales teams use AI to prioritize accounts, personalize outreach at scale, capture and coach on conversations, and forecast revenue more accurately, while keeping reps in control of relationships.
Media: Media sales teams use AI to prioritize accounts, personalize outreach at scale, capture and coach on conversations, and forecast revenue more accurately, while keeping reps in control of relationships.
Look for evidence of real pipeline or conversion lift, not just activity metrics or feature lists.
Confirm deep integration with your CRM, email, and dialer so activity is captured and acted on.
Assess the accuracy and coverage of contact, account, and intent data.
For outreach agents, verify deliverability safeguards and controls to avoid spammy, off-brand messaging.
Confirm compliance for outreach (CAN-SPAM/GDPR) and consent for call recording.
Understand seat vs. usage pricing and model expected ROI against your motion.
Sales AI is moving toward agentic SDRs that research, sequence, and engage prospects end to end with human oversight.
Conversation and intent signals are making prioritization and forecasting sharper and more real-time.
Personalization is deepening as agents ground outreach in richer account and buyer context.
Buyers should prioritize measurable pipeline impact, CRM fit, data quality, deliverability and compliance controls, and transparent governance.
Sales AI agents use machine learning and generative models to automate and assist selling, prospecting and prioritizing accounts, drafting and personalizing outreach, capturing and analyzing calls and emails, scoring leads and deals, and forecasting revenue. They exist both as standalone tools (AI SDRs, conversation intelligence, forecasting) and as AI features inside CRMs and sales-engagement platforms, designed to give reps more selling time and managers better visibility.
No, it changes their focus. AI automates research, outreach drafting, CRM data entry, and analysis, while reps concentrate on relationships, discovery, negotiation, and closing. Fully automating buyer relationships tends to backfire; the best results come from reps directing AI and reviewing its output, especially for outreach.
They can, by prioritizing the right accounts, personalizing outreach at scale, and freeing reps from busywork. But results depend on data quality, deliverability discipline, and your sales motion. Insist on evidence of incremental pipeline or conversion lift measured against a baseline, not just more emails sent or calls logged.
Good tools ground messages in real account research and CRM context, enforce deliverability best practices (warm-up, sending limits, domain health), and give you brand and review controls. Without those safeguards, mass AI outreach can hurt deliverability and brand, so evaluate quality controls and compliance carefully.
Recording laws vary by region and may require participant consent. Reputable conversation-intelligence tools provide consent and notification features, but you're responsible for complying with applicable laws and policy. Review consent handling, data residency, and retention before adopting.
Reputable vendors offer encryption, access controls, retention settings, and compliance certifications, and enterprise plans typically guarantee your data isn't used to train shared models. Given the sensitivity of CRM and conversation data, confirm data handling before connecting your systems.
Common models are per-seat (rep) subscriptions, usage-based (contacts, emails, or minutes), or add-ons within a CRM or sales-engagement platform. Estimate your team size and activity volume, and model expected ROI against your average deal size to compare true cost.
Prioritize evidence of pipeline impact, deep CRM and stack integration, data quality and enrichment, deliverability and quality controls for outreach, privacy and consent compliance, and pricing tied to ROI. Pilot with clear success metrics against a baseline before scaling across the team.
