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Agentic Lead Gen

Autonomous B2B lead generation

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open sourcediscovery agent: scanning 820 domains35 cited papers

Autonomous AI agents
that discover, enrich, and
close B2B leads

Five specialized AI agents work autonomously to find companies, enrich profiles, discover decision-maker contacts, and craft personalized outreach. Your agents work 24/7 so you don't have to.

agentic lead gen — agents active
50,000+
pages discovered
autonomous crawl agents (RL + UCB1)
300+
leads qualified
multi-agent enrichment pipeline
92%
contact accuracy
AI-verified email + LinkedIn
24x7
agent uptime
fully autonomous, zero manual work
820 domains discovered → 4,200 companies enriched → 1,100 contacts verified → 300 personalized outreach campaigns
agentic lead gen -- pipeline modules

From raw web pages to qualified B2B leads -- seven autonomous modules, zero cloud dependencies. Hover each stage to explore.

00
orchestrate

System Overview

SQLite WAL + LanceDB HNSW + ChromaDB hybrid storage in ~15 GB footprint

01
crawl

RL Crawler

DQN agent with 448-dim state + UCB1 multi-armed bandit explores 820 domains, achieving 3× harvest rate

02
extract

NER Extraction

BERT-base-cased + spaCy + BERTopic extract entities at 92.3% F1, processing ~100 pages/sec

03
resolve

Entity Resolution

Siamese 128-dim embeddings with SQLite CTEs deduplicate in <1ms ANN queries

04
score

Lead Scoring

XGBoost 50% + LogReg 25% + RF 25% ensemble scores leads with 89.7% precision

05
report

Report Generation

Local LLM agent + SQLite/ChromaDB RAG generates reports with 97% factual accuracy in 10-30s

06
evaluate

Evaluation

SHAP explanations + cascade error tracking monitor pipeline health -- keeping accuracy at scale (CER ~0.15)

00
orchestrate

System Overview

SQLite WAL + LanceDB HNSW + ChromaDB hybrid storage in ~15 GB footprint

01
crawl

RL Crawler

DQN agent with 448-dim state + UCB1 multi-armed bandit explores 820 domains, achieving 3× harvest rate

02
extract

NER Extraction

BERT-base-cased + spaCy + BERTopic extract entities at 92.3% F1, processing ~100 pages/sec

03
resolve

Entity Resolution

Siamese 128-dim embeddings with SQLite CTEs deduplicate in <1ms ANN queries

04
score

Lead Scoring

XGBoost 50% + LogReg 25% + RF 25% ensemble scores leads with 89.7% precision

05
report

Report Generation

Local LLM agent + SQLite/ChromaDB RAG generates reports with 97% factual accuracy in 10-30s

06
evaluate

Evaluation

SHAP explanations + cascade error tracking monitor pipeline health -- keeping accuracy at scale (CER ~0.15)

agentic lead gen — benchmarks

Every Agentic Lead Gen metric is measured from real pipeline runs, backed by 35 cited papers. See BENCHMARKS.md for methodology.

$1,500
annual cost
local inference — no cloud GPU bills
$1,500 local
$13,200 cloud
92%
NER F1 score
BERT-base + spaCy extraction
300
pages to leads
50K pages → 300 leads (99.4% reduction)
15%
harvest rate
3× baseline via RL crawler
1ms
ANN latency
siamese 128-dim entity resolution
89%
scoring precision
89.7% precision / 86.5% recall
97%
factual accuracy
RAG report generation via ollama
182ms
per-lead latency
end-to-end without LLM step
All benchmarks from local Agentic Lead Gen runs — no cherry-picked cloud numbers.

core capabilities

Three systems that make cloud CRMs obsolete

Cloud CRMs are optimized for their margins, not your pipeline. Agentic Lead Gen reverses that -- autonomous agents on your hardware, working 24/7.

3x harvest rate

RL-powered crawling

DQN with 448-dimensional state space and UCB1 multi-armed bandit learns which domains yield the best leads. Not keyword matching -- reinforcement learning that gets smarter every cycle.

3x more relevant pages per crawl cycle vs. random baseline

448-dim state encodes page structure, link density, and domain history

UCB1 bandit balances exploration vs exploitation across 820 domains

89.7% precision

Ensemble scoring

XGBoost 50%, logistic regression 25%, random forest 25%. Each model catches what the others miss -- with SHAP explanations and conformal prediction on every score.

4-7% higher precision-recall AUC than any single model

SHAP explanations show why each lead scored high or low

Conformal prediction gives calibrated confidence intervals

64-89% cost savings

Local-first privacy

SQLite graph + LanceDB vectors + ChromaDB embeddings -- all local. No API calls to score leads. Runs entirely on commodity hardware at $1,500/year vs $5,400-13,200 for cloud.

182ms per-lead latency, ~15 GB total footprint

Zero data leaves your infrastructure during scoring

Full pipeline with all indexes in ~15 GB footprint

Ready to deploy Agentic Lead Gen?

Autonomous agents. 300 qualified leads per cycle. Fully local. 35 cited papers.

architecture

storage

hybrid graph + vector + document store

sqlite wallancedb hnswchromadb

ML / RL

RL crawling + ensemble scoring

dqnucb1xgboostbert nersiamese

generation

local LLM report generation

ollamaragbertopic

evaluation

cascade error tracking + drift detection

shapevidently
Agentic Lead Gen is fully open source -- fork it, self-host it, extend the agents for your ICP
ready to deploy

Stop managing pipelines.
Let agents do it.

Deploy once, run forever. Your agents discover, enrich, score, and deliver qualified B2B leads around the clock — for $1,500/year total cost.

300+ qualified leads per cycle
fully autonomous — zero manual enrichment
runs on your hardware, your data stays local
deploy agentic lead gen locally
no credit card
open source
self-hosted
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