Question 1

What manual tasks can we automate when using Realaml?

Accepted Answer

You can automate the movement of verification and onboarding results from Realaml into your CRM, database, or downstream systems, eliminating manual data entry. You can also trigger conditional workflows based on verification outcomes, fraud risk scores, or onboarding status, so records flow to the right team or process without human intervention. Common automations include flagging high-risk contacts for review, updating contact records with verified identity data, or routing approved records to your operations system for next steps.

Question 2

How does data flow between Realaml and other business tools?

Accepted Answer

Realaml receives contact data or identity information from your source system, performs verification and fraud analysis, then returns results such as verification status, risk scores, and compliance data. You can configure automations to pull these results via API or webhook and push them into your CRM, data warehouse, email system, or internal databases. The flow typically moves incoming records into Realaml, waits for verification completion, then automatically syncs the enriched data back to where you need it for downstream actions.

Question 3

What problems should we watch for when automating around Realaml?

Accepted Answer

Verification and fraud detection results can take time to complete, so automations that assume instant responses may fail or create duplicate work. Data mismatches between your source system and Realaml inputs can cause verification failures or missed fraud signals. If your automation doesn't account for multiple verification statuses (pending, verified, failed, flagged), records may be processed prematurely or sent to the wrong workflow. Always test that your automation handles incomplete or ambiguous results gracefully and includes fallback steps for records that don't resolve cleanly.

Question 4

How should we structure our data and processes to make Realaml automations reliable?

Accepted Answer

Ensure your contact records are consistently formatted before they reach Realaml, with required identity fields populated and standardized. Set up clear process rules in advance: define what verification status triggers which action, which fraud risk thresholds require human review versus automatic approval, and how long you wait for results before escalating. Use a dedicated field or status column in your database to track Realaml verification state, so automations can reference it and prevent duplicate submissions. Map Realaml's response codes and risk categories to your internal workflows so downstream teams know exactly what each result means.

Automate the manual work in Realaml

Realaml by the numbers

Top 5 Realaml friction points when done manually

Manual Realaml data entry errors

Realaml records fall out of sync

Exporting Realaml data takes forever

Realaml follow-ups slip through cracks

Realaml data stays trapped in silos

What you can automate in Realaml

Create Hivelight matters when new Realaml forms are submitted

Create new LEAP (Legal) cards from completed Realaml verifications

Create new LEAP (Legal) cards from submitted realm forms

Create verifications in Realaml for new matters in Clio

Send emails in Gmail when verifications are completed in Realaml

Tools commonly connected to Realaml

Realaml Automation questions

Ready to automate your work in Realaml?