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Preisser Solutions
Revenue & MarketingLIVE

Deep prospect research in minutes — not hours of manual lookup.

A multi-agent orchestration system that deploys parallel sub-agents to research individual prospects across the web, synthesizes findings into enriched profiles, and scores source credibility — so outreach is individualized, not generic.

04 INPUTS04 OUTPUTS06 CAPABILITIES06 TECH

Personalized outreach requires knowing something real about the person you're reaching. Manual prospect research — LinkedIn, company site, Google, news search — takes 30-60 minutes per person and still misses signals scattered across sources a human wouldn't think to check. Most outreach skips the research step and sends generic messages. The Customer Research Agent makes individualized research fast enough to be practical at scale.

The agent deploys a fleet of parallel sub-agents against a single prospect. Each sub-agent searches a different source category — professional profile, company news, recent activity, public statements, industry context, social signals — and returns structured findings. A synthesis layer aggregates the parallel results, scores each source for credibility, resolves conflicts between sources, and produces a unified enriched profile: current role, recent moves, areas of focus, likely priorities, and any signals relevant to the outreach context.

The pattern was proven in the Elect Righteous research pipeline, which deploys the same parallel sub-agent architecture to research individuals across 15+ web source passes. For commercial use, the same architecture enriches CRM records for existing customers, qualifies inbound leads, and powers the individualized outreach layer for the Intelligent Outbound Sales product.

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Capabilities

  1. 01

    Parallel sub-agent deployment

    Multiple sub-agents research different source categories simultaneously — no sequential single-source lookup, parallel passes across professional, news, social, and industry sources.

  2. 02

    Source credibility scoring

    Each source is scored for credibility and recency before its findings enter the synthesized profile — high-confidence recent signals weighted over outdated or low-quality sources.

  3. 03

    Schema-validated profile output

    Research outputs conform to a defined profile schema — current role, company context, recent activity, areas of focus, signals — ready for downstream system integration.

  4. 04

    CRM record enrichment

    Enriched profiles write back to existing CRM records, upgrading sparse contact records with researched context for existing customers or leads.

  5. 05

    Inbound lead qualification

    Researches inbound leads immediately on capture — so the sales team receives a qualified, enriched record rather than a bare form submission.

  6. 06

    Outreach material generation

    Researched profile context feeds directly into hyper-personalized outreach generation — each message references something real about the prospect.

How it works

  1. 01

    Prospect intake

    A prospect name and company enter the system — from a CRM record, a manual input, or an inbound lead capture trigger.

  2. 02

    Parallel sub-agent deployment

    Sub-agents deploy simultaneously across configured source categories — professional profile, company news, recent activity, social signals, industry context.

  3. 03

    Findings aggregation

    Each sub-agent returns its findings as structured data. The synthesis layer aggregates across all parallel results, resolving conflicts between sources.

  4. 04

    Source scoring and profile assembly

    Each finding is scored for credibility and recency. The final profile assembles from the highest-confidence signals across all source categories.

  5. 05

    Output delivery

    The enriched profile delivers as structured JSON, writes back to the CRM record, or feeds directly into the outreach generation layer.

Inputs & Outputs

What it takes in

  • Prospect name and companyCRM record / CSV / API
  • Research context and target signal typesConfiguration
  • Source categories to searchConfiguration
  • CRM connection for record enrichment (optional)API / webhook

What it sends out

  • Enriched prospect profile with source citationsJSON / CRM write-back
  • Source credibility scores per findingStructured data
  • Signals relevant to outreach contextStructured profile section
  • Updated CRM record with enriched fieldsCRM write-back

Use cases

  • Use this when manual prospect research is a bottleneck — each qualified prospect requires 30-60 minutes of lookup before outreach can be personalized.

  • Use this when your CRM contains sparse contact records and you want to enrich them with researched context without manual investigation.

  • Use this when inbound leads arrive as bare form submissions and the sales team needs enriched context before the first conversation.

  • Use this when outbound outreach is generic because the research step is too slow to do at scale.

  • Use this as the upstream research layer feeding the Intelligent Outbound Sales product's personalized message generation.

Related works

Intelligent Outbound Sales

Researches prospects, drafts personalized cold outreach, and sequences across email and SMS — tuned to one business's offer and voice.

Revenue & Marketing

Customer Reactivation Agent

Cleans dormant lists, segments, and runs hyper-personalized SMS + email outreach daily.

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MarCommand — Multi-Channel Marketing Engine

An 8-agent marketing system: content, copy, design, paid, AEO, analyst, QA, orchestrator.

Flagship Platforms

Want deep prospect research in minutes instead of hours?

Preisser Solutions builds customer research agents configured to your prospect profile and CRM stack. The first conversation covers your current research process and what individualized outreach would require.

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