AI agents parse messy inbound requests, enforce strict naming conventions, and ensure pristine data hygiene before information ever enters your enterprise Salesforce or HubSpot instance.
5 hrs
saved/day
vs. manual ops
18
validation checks
per record
12+
enriched fields
via Clearbit
< 30s
per record
end-to-end
Typical build: 3–4 week sprint · Fixed price · Zero delivery risk
Sources
4 inbound types
Validation
18 checks
Speed
< 30s / record
One misspelled company name creates duplicate accounts. One non-standard phone format breaks your dialler. One wrong deal stage skews your entire pipeline forecast. Manual ops teams cannot keep up with inbound volume.
Without MX record checks, fake emails fill your nurture sequences. Without duplicate detection, the same contact gets three follow-up sequences. Without taxonomy enforcement, your reporting segments collapse.
Your ops team spends 15 minutes per contact searching LinkedIn, Crunchbase, and company websites to fill in the firmographic fields your CRM needs for segmentation and scoring. At 50 records per day, that is 12+ hours of research.
This is the actual workflow Kovil AI builds and deploys — not a diagram. Here is what runs inside every node.
Inbound records arrive from four possible sources: web forms (Typeform/HubSpot forms), email forwarded to a dedicated parsing inbox, CSV bulk uploads dragged into a Slack channel, or API direct POST from partner systems. n8n captures all four via dedicated trigger nodes and routes them into a single normalisation pipeline. No source is missed — even poorly formatted CSVs with misaligned columns are accepted and queued for parsing.
GPT-4o receives the raw record and is given a strict JSON schema matching the target CRM field structure. It extracts and maps every field: company name to normalised format (full legal name — no Inc. or Ltd abbreviations), contact name to first/last split with proper capitalisation, phone to E.164 international format, industry to a standardised taxonomy of 24 approved categories, and deal stage to the correct CRM pipeline stage name. Output is always structured JSON, never free text.
A rule-based validator runs 18 checks against the parsed record: required fields present, email format valid including MX record check (not just regex), phone number dialable, company name not on blocklist, deal value within acceptable range, no duplicate contact email in CRM, and industry matching the approved taxonomy. Records failing critical checks (invalid email, duplicate) are rejected with a specific error code and routed to Slack for ops review. Records failing soft checks are flagged but allowed through.
For contacts with a valid business email, n8n calls the Clearbit Enrichment API to append firmographic data: company employee count, annual revenue estimate, tech stack (tools the company uses), LinkedIn URL, company description, and HQ location. Enrichment adds an average of 12 additional data points per contact — without any manual research. Contacts with personal email addresses (Gmail, Yahoo) skip enrichment and pass through with available data only.
The clean, enriched record is pushed to the target CRM via API. Duplicate detection runs first: if a contact with the same email already exists, the record is UPDATED rather than creating a duplicate. New contacts are CREATED with all fields populated and properly mapped to the CRM field taxonomy. Deals are created in the correct pipeline stage with the correct owner assigned based on territory and industry rules configured during setup.
Every record processed is logged to a dedicated #crm-ops-log Slack channel with a status emoji: clean and written to CRM, written with a soft flag noting the missing field, or rejected with the specific reason. For rejections, the Slack message includes the specific validation failure and the raw data so the ops team can fix and resubmit. A weekly digest is posted every Monday: total records processed, pass rate, and top failure reasons for the week.
Orchestration
Captures all four inbound sources, routes records through the normalisation pipeline, and manages all branch logic for pass/flag/reject paths.
Field parser
Receives raw record and outputs structured JSON matching exact CRM field schema. Handles messy, inconsistent input formats from any source.
Data enrichment
Appends 12+ firmographic fields per contact via Enrichment API — employee count, revenue, tech stack, LinkedIn URL, HQ location.
CRM target
Receives clean, validated, enriched records via API. Upsert logic prevents duplicates. Owner and pipeline stage assigned automatically.
CRM target
Alternative CRM target. Same upsert logic, same field taxonomy mapping, same pipeline stage assignment via HubSpot API.
Audit + ops
Receives every record outcome with full context. Ops team can review rejections and resubmit corrected records from the channel.
Custom rules (built by Kovil)
18-rule custom validator: MX record checks, duplicate detection, blocklist lookup, deal value range, industry taxonomy matching.
Kovil AI scopes, builds, tests and deploys this workflow end-to-end. You do not touch n8n until it is live and processing records cleanly.
The 18 checks cover: required fields present (company name, primary email, phone), email format valid, MX record check (the email domain must have active mail servers), phone number dialable in E.164 format, company name not on the configured blocklist, deal value within acceptable range, no duplicate contact email in CRM, industry matches the approved taxonomy of 24 categories, deal stage matches CRM pipeline stage names, first and last name split correctly, website URL resolvable, country code ISO 3166-1 compliant, and six custom business-logic rules configured per client.
Yes. The workflow can be configured to write to either CRM or both simultaneously. For agencies managing clients on different CRM platforms, the routing logic uses the client identifier to determine the correct CRM target for each record.
Hard failures (invalid email, confirmed duplicate, blocklisted company) are rejected and logged to the Slack #crm-ops-log channel with a specific error code. The ops team can correct the record and resubmit via a dedicated Slack action. Soft failures (missing optional field, unresolvable website) are allowed through with a flag visible in the CRM record.
For contacts with a valid business email, n8n calls the Clearbit Enrichment API and appends 12+ firmographic fields: employee headcount, estimated annual revenue, funding stage, tech stack (tools the company uses), LinkedIn company URL, industry classification, and HQ address. This eliminates manual research and ensures every CRM contact is fully populated on entry.
Book a 30-minute discovery call. We will scope the validation rules, CRM field schema, and Clearbit enrichment logic for your specific Salesforce or HubSpot setup — fixed price, zero delivery risk.
Typical sprint: 3–4 weeks · Fixed-price · Fully managed delivery · Post-launch support included