How does the Master Orchestrator route data through the AI lead generation pipeline?

For batches of 50 or fewer companies, all 12 stages execute inline within the orchestrator for maximum speed. For larger datasets, the orchestrator chains specialized actor engines via Apify Actor.call(), with each actor reading its input from the previous actor's output Named Dataset.

What are the 4 pipeline modes for B2B sales intelligence?

Full mode runs all 5 engines end-to-end. Discovery Only finds companies and validates domains. Enrich Only skips discovery for datasets that already have domains. Verify Only runs the email verification API on an existing email list. Each mode can also skip specific stages via configuration.

How does checkpoint/resume prevent data loss in the lead enrichment platform?

Every 50 processed items, the orchestrator writes a checkpoint to Apify KV Store. If the run crashes or is manually stopped, restarting with resume=true skips all already-processed items and continues from the last checkpoint. This ensures no wasted compute in the AI lead generation pipeline.

Can I trigger the sales intelligence API via webhook?

Yes. The orchestrator supports webhook delivery: on pipeline completion, it POSTs a payload containing run status, total records processed, processing time, output dataset ID, and download links. This enables integration with CRM systems, Slack notifications, or downstream AI outbound automation workflows.

Master Orchestrator - AI Lead Generation Pipeline Controller

Step 1

Input Resolution

Priority-based input parsing for the lead enrichment platform: inline company array -> existing Apify Dataset -> KV Store file -> HTTP URL download. Smart column detection for CSV/Excel.

Step 2

Route Planning

Analyzes batch size and input type for AI lead generation. <=50 companies: inline 12-stage processing. >50 companies: actor-chain delegation via Actor.call() through the sales intelligence API.

Step 3

Pipeline Execution

4 modes for B2B sales intelligence: Full (all 5 engines), Discovery Only, Enrich Only (skip discovery), Verify Only (email verification API). Stage skipping via configuration.

Step 4

Checkpoint Management

Progress saved to KV Store every 50 items and on graceful shutdown. Resume skips already-processed items for reliable AI lead generation. Format: checkpoint-{actor}-{run_id}.

Step 5

Result Aggregation

Collects outputs from all actor stages in the lead enrichment platform. Merges partial results. Computes pipeline-level statistics for the web scraping pipeline.

Step 6

Delivery

Final output to Apify Named Dataset. Optional webhook POST with completion status, record count, and download URL via the sales intelligence API.

Step 1

Input Resolution

Priority-based input parsing for the lead enrichment platform: inline company array -> existing Apify Dataset -> KV Store file -> HTTP URL download. Smart column detection for CSV/Excel.

Step 2

Route Planning

Analyzes batch size and input type for AI lead generation. <=50 companies: inline 12-stage processing. >50 companies: actor-chain delegation via Actor.call() through the sales intelligence API.

Step 3

Pipeline Execution

4 modes for B2B sales intelligence: Full (all 5 engines), Discovery Only, Enrich Only (skip discovery), Verify Only (email verification API). Stage skipping via configuration.

Step 4

Checkpoint Management

Progress saved to KV Store every 50 items and on graceful shutdown. Resume skips already-processed items for reliable AI lead generation. Format: checkpoint-{actor}-{run_id}.

Step 5

Result Aggregation

Collects outputs from all actor stages in the lead enrichment platform. Merges partial results. Computes pipeline-level statistics for the web scraping pipeline.

Step 6

Delivery

Final output to Apify Named Dataset. Optional webhook POST with completion status, record count, and download URL via the sales intelligence API.

Step 1

Input Resolution

Priority-based input parsing for the lead enrichment platform: inline company array -> existing Apify Dataset -> KV Store file -> HTTP URL download. Smart column detection for CSV/Excel.

Step 2

Route Planning

Analyzes batch size and input type for AI lead generation. <=50 companies: inline 12-stage processing. >50 companies: actor-chain delegation via Actor.call() through the sales intelligence API.

Step 3

Pipeline Execution

4 modes for B2B sales intelligence: Full (all 5 engines), Discovery Only, Enrich Only (skip discovery), Verify Only (email verification API). Stage skipping via configuration.

Step 4

Checkpoint Management

Progress saved to KV Store every 50 items and on graceful shutdown. Resume skips already-processed items for reliable AI lead generation. Format: checkpoint-{actor}-{run_id}.

Step 5

Result Aggregation

Collects outputs from all actor stages in the lead enrichment platform. Merges partial results. Computes pipeline-level statistics for the web scraping pipeline.

Step 6

Delivery

Final output to Apify Named Dataset. Optional webhook POST with completion status, record count, and download URL via the sales intelligence API.

LeadsLogix Dashboard

Live

+12%

24,847

Leads

+8%

18,293

Verified

+15%

6,142

Companies

+22%

$2.8M

Pipeline

Pipeline78%

Discover

Crawl

Extract

Verify

Score

FAQ

Frequently Asked Questions

Everything you need to know about our platform.

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Explore More

Platform Architecture

Platform

Full overview of the AI lead generation pipeline architecture

/platform

12-Stage Pipeline

Platform

Every stage the orchestrator manages in the lead enrichment platform

/platform/enrichment

Data Enrichment

Solution

End-to-end B2B data enrichment with pipeline orchestration

/solutions/data-enrichment

LeadsLogix vs Clay

Compare

Unified orchestration vs manual waterfall for AI outbound automation

/compare/vs-clay

All Actor Engines

Platform

The 6 engines coordinated by the B2B sales intelligence orchestrator

/platform/actors

Pricing

Plans for the AI lead generation platform

/pricing

B2B Discovery Engine Contact Intelligence Engine Email Intelligence Engine AI Qualification Engine Export Center

Start Using the Actor Engine 6 of 6 - Controller Engine

Deploy this engine in minutes. No configuration required — just provide your data and let the pipeline handle the rest.

Step 1

Input Resolution

Priority-based input parsing for the lead enrichment platform: inline company array -> existing Apify Dataset -> KV Store file -> HTTP URL download. Smart column detection for CSV/Excel.

Step 2

Route Planning

Analyzes batch size and input type for AI lead generation. <=50 companies: inline 12-stage processing. >50 companies: actor-chain delegation via Actor.call() through the sales intelligence API.

Step 3

Pipeline Execution

4 modes for B2B sales intelligence: Full (all 5 engines), Discovery Only, Enrich Only (skip discovery), Verify Only (email verification API). Stage skipping via configuration.

Step 4

Checkpoint Management

Progress saved to KV Store every 50 items and on graceful shutdown. Resume skips already-processed items for reliable AI lead generation. Format: checkpoint-{actor}-{run_id}.

Step 5

Result Aggregation

Collects outputs from all actor stages in the lead enrichment platform. Merges partial results. Computes pipeline-level statistics for the web scraping pipeline.

Step 6

Delivery

Final output to Apify Named Dataset. Optional webhook POST with completion status, record count, and download URL via the sales intelligence API.

Step 1

Input Resolution

Priority-based input parsing for the lead enrichment platform: inline company array -> existing Apify Dataset -> KV Store file -> HTTP URL download. Smart column detection for CSV/Excel.

Step 2

Route Planning

Analyzes batch size and input type for AI lead generation. <=50 companies: inline 12-stage processing. >50 companies: actor-chain delegation via Actor.call() through the sales intelligence API.

Step 3

Pipeline Execution

4 modes for B2B sales intelligence: Full (all 5 engines), Discovery Only, Enrich Only (skip discovery), Verify Only (email verification API). Stage skipping via configuration.

Step 4

Checkpoint Management

Progress saved to KV Store every 50 items and on graceful shutdown. Resume skips already-processed items for reliable AI lead generation. Format: checkpoint-{actor}-{run_id}.

Step 5

Result Aggregation

Collects outputs from all actor stages in the lead enrichment platform. Merges partial results. Computes pipeline-level statistics for the web scraping pipeline.

Step 6

Delivery

Final output to Apify Named Dataset. Optional webhook POST with completion status, record count, and download URL via the sales intelligence API.

Step 1

Input Resolution

Priority-based input parsing for the lead enrichment platform: inline company array -> existing Apify Dataset -> KV Store file -> HTTP URL download. Smart column detection for CSV/Excel.

Step 2

Route Planning

Analyzes batch size and input type for AI lead generation. <=50 companies: inline 12-stage processing. >50 companies: actor-chain delegation via Actor.call() through the sales intelligence API.

Step 3

Pipeline Execution

4 modes for B2B sales intelligence: Full (all 5 engines), Discovery Only, Enrich Only (skip discovery), Verify Only (email verification API). Stage skipping via configuration.

Step 4

Checkpoint Management

Progress saved to KV Store every 50 items and on graceful shutdown. Resume skips already-processed items for reliable AI lead generation. Format: checkpoint-{actor}-{run_id}.

Step 5

Result Aggregation

Collects outputs from all actor stages in the lead enrichment platform. Merges partial results. Computes pipeline-level statistics for the web scraping pipeline.

Step 6