AI Intent-Based Prospecting That Fills Your Queue With In-Market Accounts
Describe your ICP in plain English and Swan's AI agent monitors your prospect universe, surfaces in-market accounts, and builds a prioritized queue ready to work. No research required.
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Why Most SDR Teams Spend Their Day Chasing the Wrong Accounts
Without an AI agent doing the signal monitoring and filtering, SDRs build research queues on instinct. The accounts that are actually in-market today go unworked.
Manual research misses signals
A list built yesterday is already cold. By the time a rep researches the company and finds contacts, the signal has cooled. Manual prospecting is always one step behind.
No live account visibility
500 ICP accounts tells you who fits. It doesn't tell you who's in-market today. SDRs can't distinguish active evaluators from accounts that haven't moved in months.
Tools never talk together
Intent data in one tool. Firmographics in another. Hiring signals in a third. SDRs spend 30-40% of their day stitching sources together just to figure out who to call.
AI Intent-Based Prospecting That Builds the Queue So SDRs Can Work It
Swan is the context and orchestration layer between your signal sources and your SDR team. It monitors your prospect universe, filters ICP-matched accounts showing live signals, and delivers a research-ready queue every morning, autonomously.
Always-on signal monitoring
Swan watches every account in your target market for intent signals: pricing page visits, funding announcements, hiring surges, and G2 activity. The moment an account crosses your threshold, Swan queues it.
Research done before opening
When Swan flags an account, it pulls firmographic context, maps stakeholders, finds verified contact info, and summarizes why the account is signaling. Research is done before the rep opens the record.
Scoring filters the noise
Swan evaluates every flagged account against your ICP: company size, industry, tech stack, and growth stage. Only accounts clearing your threshold reach the queue. Reps see high-confidence accounts, not noise.
Let the numbers talk
Before & After Swan
Before Swan
An SDR pulls a CRM list, cross-references an intent tool, checks LinkedIn, and manually Googles each company. Two hours of research to surface three accounts worth calling. By the time the rep dials, two signals have already gone cold.
After Swan
What took days takes minutes. Describe your ICP and signal criteria in plain English. Swan handles the monitoring, the research, and the scoring. No manual source-stitching, no wasted hours on cold accounts. Just a prioritized queue of in-market accounts ready to work, every morning.
If You Can Write It,
Swan Can Build It.
Describe your intent-based prospecting criteria like you're briefing a new SDR. Swan turns your words into a live signal-monitoring and prioritization workflow instantly.
Intelligence,
Not Automation.
raditional tools surface a signal and hand it off raw. Swan evaluates account fit across multiple data dimensions and builds a research brief the way a senior SDR manager would.
Adapts in seconds,
not months.
Your ICP and signal criteria evolve as you learn what converts. Just tell Swan what changed and the workflow updates instantly.
Connects to Every Signal Source Your Team Already Uses
Swan pulls intent signals, hiring data, funding events, and firmographic context from your prospecting stack into one prioritized queue. Your SDR team never stitches tools together manually.
Loved by teams scaling smarter, not bigger
FAQs
What is an AI agent for intent-based prospecting?
An AI agent for intent-based prospecting is an autonomous researcher that monitors your prospect universe, detects buying signals, scores accounts against your ICP, and delivers a pre-researched queue to your SDR team, without manual work at any step.
- It monitors hundreds or thousands of accounts simultaneously across multiple signal sources
- It filters signal noise using your ICP criteria so only qualified accounts reach the queue
- It pulls firmographic context, maps decision-maker contacts, and finds verified contact information at signal time
- It attaches a context brief to every flagged account so reps open records already knowing why the account flagged
- It updates the workflow autonomously when your criteria change
Unlike a manual research process, an AI agent never sleeps, never falls behind, and never skips an account because the workday ended.
How is intent-based prospecting different from account prioritization?
Account prioritization ranks accounts already in your pipeline or CRM. Intent-based prospecting finds and surfaces new accounts from your broader ICP universe that aren't yet in play.
- Prioritization works on existing records; prospecting sources net-new accounts from the market
- Intent-based prospecting triggers on first-time signals from accounts your team may never have touched
- Prioritization helps reps decide where to focus today; prospecting determines who enters the pipeline at all
- Swan handles both, but they run as separate workflows with different triggers and data sources
- The two motions are complementary: prospecting fills the top of the funnel, prioritization moves accounts through it
If you're running both, Swan connects them so a prospected account flows directly into the prioritization queue once it enters your CRM.
Does Swan replace my intent data tools like 6sense or RB2B?
No. Swan sits on top of your intent data tools and acts on the signals they surface.
- 6sense and RB2B detect intent signals; Swan decides which signals meet your ICP criteria and are worth acting on
- Without an orchestration layer, intent data requires manual review before it reaches an SDR
- Swan handles the step between signal detection and a researched, scored account in the SDR queue
- Every intent signal that clears your criteria triggers enrichment, stakeholder mapping, and ICP scoring without human intervention
- Your existing intent data investment becomes more valuable, not redundant
Think of Swan as the execution layer that turns your intent data from a dashboard into a live prospecting queue.
How does Swan decide which accounts make it into the SDR queue?
Swan evaluates every flagged account against the full ICP criteria you define: firmographics, tech stack, company stage, and signal strength.
- Accounts must match your ICP filters (industry, employee count, growth stage, tech stack) before any signal triggers enrichment
- Signal strength thresholds are configurable: a single pricing page visit may not qualify, but three visits from two contacts in 48 hours does
- Swan cross-references multiple signals on the same account to increase confidence before queuing
- Accounts that fail ICP criteria are filtered out before they ever reach the queue, keeping signal-to-noise ratio high
- You can update the threshold criteria in plain English at any time and the filter applies immediately
The goal is a short list of high-confidence accounts, not a firehose of everything that moved.
How do I know which accounts my SDRs should be calling today?
Prioritize accounts that are showing active buying signals. Three pricing page visits from the same company in 48 hours beats a perfect ICP match that hasn't moved in months. Signal recency is the best predictor of a reply.
Swan monitors your entire ICP universe and queues the hottest accounts every morning. Your reps open their day knowing exactly who to call.
Why are my SDRs getting low reply rates even with personalized outreach?
Timing. A well-written email sent to someone not actively evaluating anything gets ignored every time. Personalization tells them you did your homework. Relevance tells them you caught them at the right moment. Signals give you that.
Swan fires outreach the moment an account shows intent, so the message lands when the prospect is already thinking about the problem. That's the difference between a 2% and a double-digit reply rate.