Inbound demand is often lost or delayed because human SDRs are unavailable, slow to respond, or inconsistent in handling calls. Many teams lack the capacity to answer inbound calls 24/7, leading to missed opportunities, poor first impressions, and wasted marketing spend. AI Inbound Calling exists to ensure every inbound call is answered immediately, consistently, and in a way that aligns with the company's sales process.

Prospects call dedicated AI SDR numbers. The AI engages in real-time, natural voice conversations, conducting discovery, qualifying leads, handling objections, and answering questions. It guides calls towards booking meetings or campaign routing. Conversations are contextual, logged, and integrated with the platform for analytics and follow-up.

You can capture and qualify inbound demand 24/7 without relying on human SDR availability. This increases lead conversion, improves response speed, and ensures a consistent inbound experience for prospects. Teams can scale inbound volume confidently, reduce operational costs, and turn inbound calls into a reliable, automated revenue channel.

Building high-quality prospect lists traditionally requires deep familiarity with filters, data schemas, and rigid search logic. This creates friction for many users and slows down list creation, often resulting in incomplete or inaccurate targeting. This feature exists to remove that complexity and allow users to focus on who they want to reach rather than how to configure searches.

We built an AI-powered search experience that allows users to describe their ideal customers using natural language. The AI BDR agent interprets the intent behind the request and automatically applies the appropriate people and company filters across the database. The system translates human intent into structured search logic, continuously refining results to match the user's criteria.

You can build accurate prospect lists faster and with less effort, even without deep technical knowledge of filtering systems. This reduces setup time, improves targeting quality, and helps you launch campaigns more quickly with greater confidence.

Sending the same message repeatedly at scale increases the risk of spam detection, deliverability issues, and prospect fatigue. Writing dozens of unique templates manually is time-consuming and difficult to maintain. Spintax exists to solve the uniqueness problem without increasing writing effort.

We implemented a spintax formatting system that allows users to create multiple variations of a message from a single template using bracketed syntax. Words, phrases, or full sentences can be rotated dynamically, producing unique versions of each message while preserving overall intent and structure.

You can safely scale outbound volume with improved deliverability and less repetitive messaging. This helps protect sender reputation, increase engagement, and reduce the manual effort required to maintain variation across campaigns.

Inbound LinkedIn replies often require fast, thoughtful responses to maintain momentum. Manually monitoring LinkedIn inboxes is time-consuming and inconsistent, leading to delayed replies and missed opportunities. This feature exists to ensure inbound conversations are handled promptly and consistently.

We built AI SDR agents that automatically analyze inbound LinkedIn messages, understand intent and conversation context, and generate appropriate replies aligned with campaign goals. Responses are sent automatically, extending automation beyond outbound into real-time conversational engagement.

You can respond instantly to LinkedIn replies without constant inbox monitoring. This improves response times, increases engagement rates, and allows you to scale LinkedIn outreach without additional manual effort.

Outreach performance is directly limited by data quality. Incomplete phone numbers, inaccurate titles, weak industry classification, and missing keywords reduce connect rates, personalization depth, and AI effectiveness. V2 exists to remove data quality as a bottleneck across the platform.

We are rebuilding the underlying data layer to significantly improve accuracy and coverage across people and company records. This includes higher phone number fill rates, standardized and more reliable job titles, improved industry mapping, and richer keyword enrichment. These improvements apply across search, enrichment, and AI workflows.

You get more usable leads per search, stronger personalization, and better results across calling, email, LinkedIn, and AI-driven workflows—without relying on external enrichment tools.

Aggregate campaign metrics hide what actually works. Without visibility into individual steps and variants, teams are forced to guess which copy, channel, or timing decisions drive results.

We built analytics that break performance down to the step and variant level across multichannel sequences. Users can compare engagement metrics for each variation to identify patterns and winning strategies.

You can optimize campaigns with confidence, double down on what works, and iterate faster using data instead of intuition.

Basic metrics don’t explain why campaigns succeed or fail. Users need clearer attribution and more trustworthy data to understand performance and ROI.

We are improving bounce tracking, campaign attribution logic, launch-date visibility, and landing page analytics to create a more reliable analytics foundation across the platform.

You gain a clearer understanding of what drives replies, meetings, and pipeline—enabling better decisions, reporting, and forecasting.

Email validity degrades over time, especially in long-running campaigns. One-time validation is not enough to protect deliverability.

Users can define how frequently emails are re-validated within a campaign. The system automatically checks email health before sends based on these rules.

Lower bounce rates, stronger sender reputation, and safer outbound scale—without manual intervention.

Rigid data schemas limit personalization and advanced automation. Teams often have valuable proprietary data they can’t easily use in outreach.

We allow users to upload and reference unlimited custom fields across sequences, AI prompts, and personalization logic.

You can personalize outreach using your own data and unlock more advanced automation without platform constraints.

Teams reinvent the wheel when creating campaigns, leading to inconsistent quality and slower execution.

We are building centralized libraries for email, LinkedIn, and full multichannel sequence templates that can be reused and customized.

Launch campaigns faster, standardize best practices, and scale what already works across your team.

Manual research and enrichment slow down pipeline generation and limit scale.

The AI agent enriches contacts, fills missing data, and identifies lookalike prospects based on ICP patterns and performance signals.

Spend less time researching and more time engaging high-quality prospects.

Unchecked bounce rates can damage sender reputation before teams notice a problem.

The system monitors campaign health in real time and automatically pauses campaigns when thresholds are exceeded, with clear alerts and logs.

Your deliverability is protected automatically, reducing risk and manual oversight.

Managing complex multichannel sequences becomes difficult as campaigns scale.

We redesigned the sequence experience with clearer UI/UX and more flexible underlying logic to support advanced automation.

Build, understand, and manage complex sequences with less friction and fewer mistakes.

Cold outreach is far less effective without signals that prospects are actually in-market.

We expanded intent coverage with hundreds of categories, thousands of topics, and AI-powered search to surface real-time buying signals.

Focus outreach on accounts that are already showing interest, improving relevance and conversion.

Static lists slow down day-to-day workflows and force users to jump between tools.

Lists now support custom columns, saved views, and in-list enrichment actions.

Lists become an active workspace for segmentation, enrichment, and execution.