Data enrichment

Enrichment fills the gaps in your CRM automatically: missing email addresses, phone numbers, LinkedIn profiles, job details, and AI-researched context. Instead of paying for a separate data tool and importing CSVs, you enrich records where they live: from a table, inside a sequence, or in a workflow.

What enrichment can find

Contact information

• Find email address (and reverse email lookup)
• Find mobile phone / direct landline (and reverse phone lookup)
• Find LinkedIn URL (plus X/Twitter, GitHub)

LinkedIn intelligence

• Person profile details: seniority, department, location
• Work history
• Recent posts (person and company), reactions and comments
• Company LinkedIn profile
• Job search signals

AI research

• Summarize a profile
• Personalized opener / personal outreach message, generated per contact
• Find people via AI research: answer questions like "Who is the CEO of this company and what is their LinkedIn URL?"

Running enrichment in bulk

Select records in a table view and choose Enrich & clean:

1. Pick the enrichment options you want
2. Dalil shows the credit cost before you run

Two behaviours keep costs down:

• Skip-if-present: options are skipped for records that already have the data, so credits are only spent where enrichment is actually needed. Turn on Overwrite per option if you want to refresh existing data (that does use credits).
• Automatic ordering: Dalil decides the order per record based on what it already has: it finds the LinkedIn URL first, then runs the email, phone, and profile lookups that depend on it.

Custom AI prompts

Beyond the standard operations, you can run custom prompt enrichment:

1. Write a prompt describing the voice, the angle, what to reference, and how to fill each output field
2. Pick which CRM fields the AI reads as input
3. Pick which text fields it writes into
4. Save prompts to your library and reuse them across runs

This is how teams generate research summaries, qualification notes, or personalisation snippets at scale. The output lands directly in fields that sequence variables can use.

Enrichment inside automation

• Sequences: the Enrich step finds missing data mid-campaign and acts as a gate: if enrichment can't find the data (and it didn't already exist), the contact's run stops instead of proceeding to a send step that would fail. See Designing flow with conditions.
• Workflows: the Enrich data action enriches records as part of any flow, and the Enrichment trigger starts workflows based on the outcome: Found, Not found, Already present, or Already attempted. The classic pattern: when enrichment finds an email → add the contact to a sequence (examples).
• Notifications: enrichment completion shows up in your notifications.

Credits

Enrichment runs on your workspace's credit balance:

• Your plan includes a monthly credit allowance; you can buy one-time top-ups in credit bundles (secure checkout via Stripe)
• Top-up credits never expire
• The credit cost is always shown before a run, and skip-if-present means you never pay for data you already have

Key outcome

Enrichment turns a sparse contact list into a workable one (reachable emails, phones, LinkedIn context, AI-written research) without leaving Dalil. Combined with sequences and workflows, it closes the loop: find the data, qualify the contact, start the outreach, all automatically.