✦ Sift · IDENTIFY Phase

The intelligence gap

“Most outreach fails not because the message is wrong — but because the context is missing. SDRs spend 20 minutes per lead doing research that should have been automated before the lead was ever assigned.”

Every lead Scribe touches
arrives enriched, profiled,
and ready to convert.

Sift enriches every Scout lead with verified phone data, LinkedIn signals, company news, and persona intelligence — so your sequences are built on context, not guesses. Shorter sales cycles. Higher reply rates. Better CAC.

Get the Full Intelligence Stack →
0%
Segmentation Accuracy
0+
Data Sources Per Lead
0
Unknown Personas Proceed
ReoonFirecrawlLinkedInApolloHubSpotSupabaseScoutAZLeadsLimadataReoonFirecrawlLinkedInApolloHubSpotSupabaseScoutAZLeadsLimadata
The Role Sift Replaces

$5,500–8,000/mo in enrichment stack
and analyst headcount. Replaced at $399/mo.

Sift consolidates Clay's enrichment automation, Clearbit's data API, and your data analyst's 20-minutes-per-lead research workflow into one continuous intelligence layer — running before any sequence is ever written.

Without Sift
✕SDR spends 20 min researching each lead before writing one email
✕Leads arrive with a name, company, and nothing else
✕Sequences built on assumptions — openers miss, replies flat-line
✕Clay $400/mo + Clearbit $1,250/mo + data analyst $4–6K/mo
✕Unknown personas proceed to outreach — segments break
With Sift ✦
✦Every lead enriched before Scribe writes a single word
✦Phone, LinkedIn signals, persona, news, and confidence score shipped
✦91% segmentation accuracy — Scribe writes to the right buyer, every time
✦Full capability at $399/mo — up to 95% cost reduction
✦Zero unknown personas proceed — M02B zero-tolerance gate

Cost equivalence: Clay ($400/mo) + Clearbit ($15K/yr ÷ 12 = $1,250/mo) + data analyst headcount ($4,000–6,000/mo) = $5,650–7,650/mo minimum.

How It Works

From Scout lead to
fully enriched intelligence card.

STEP 01
Receive the Scout Shortlist

Sift ingests every account and lead Scout surfaces — ICP-matched, signal-ranked, and ready for deep enrichment. No cold lists. No CSVs. Only pre-qualified prospects enter the pipeline.

STEP 02
Multi-Source Enrichment

Sift cross-references 50+ data sources simultaneously: Reoon for phone verification, Firecrawl for live company news, LinkedIn for activity signals and connection depth, Apollo for firmographics. Each field is confidence-scored.

STEP 03
Persona & ICP Taxonomy QA

M02B applies zero-tolerance classification: every lead is mapped to a department family and buying role. If a persona can't be determined with confidence, the lead is flagged — never forwarded with unknown context.

STEP 04
Enriched Intelligence Card → Scribe

Each lead exits Sift as a verified intelligence card: phone, persona, LinkedIn signals, recent company news, and an enrichment confidence score (0–100). Scribe receives context, not a name.

✦ Enrichment Card — Signature Visual
✦ Sift · Lead Intelligence Card
SPARSE
Before Sift — sparse record
NameJordan Walsh
CompanyDataflow Inc.
Emailjordan@dataflow.com
Phone—
LinkedIn—
Persona—
Signal—
Company News—
Enrichment Score—

Scroll to trigger the enrichment reveal. Each field populates in sequence as Sift completes its 50+ source cross-reference — ending with the enrichment confidence score that gates handoff to Scribe.

Use Cases

Four ways Sift
closes the intelligence gap.

USE CASE 01
Pre-Sequence Intelligence

Every lead Scout surfaces is enriched before Scribe writes a single touchpoint. Sift eliminates the 20-minute SDR research window — sequences launch with full context from day one.

USE CASE 02
Persona Auditing

Run Sift against an existing lead list to validate persona classifications. Zero unknown roles, zero mismatched department tags before a campaign launches. Scribe writes to the right buyer every time.

USE CASE 03
Competitive Trigger Detection

Firecrawl ingests company news continuously — funding rounds, leadership changes, product launches, competitive tech stack mentions. Sift surfaces the hiring signal before your comp finds out.

USE CASE 04
Pipeline Hygiene

Re-enrich stale CRM leads with fresh phone data, updated LinkedIn signals, and current company context. Recycle dormant contacts into active, accurately-profiled pipeline.

Proof Metrics
91%
accuracy
Segmentation accuracy on first-pass persona classification
50+
data sources
Data sources enriched per lead simultaneously across phone, LinkedIn, news, and firmographics
0
unknown personas
Unknown personas that proceed to Scribe — M02B zero-tolerance gate enforced on every lead
20 min
per lead saved
Average SDR research time eliminated per lead — returned to your reps for conversations
Sequences Without Sift

“Scribe writes with assumptions. The personalization is surface-level. Your opener is generic because the context wasn't there. The SDR still spends 20 minutes per lead doing research that could have been done before the lead was ever assigned. Your sequences sound like templates — because they're built on template-level data.”

Sequences With Sift

“Scribe opens with the Series B they just closed, references the two AE hires Signal caught, and addresses the VP Revenue persona directly. Replies come in because the lead felt seen — not sold. The research was done before the sequence was even assigned.”

FAQ

Common questions
about Sift.

Sift · Now Accepting Early Access

Stop letting context-free leads
kill your send rates and cycles.

Sift is part of the Scout + Sift intelligence stack. Request access and we'll run a live Scout scan plus enrichment pass on your ICP — you see your leads fully profiled before you commit.