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Agentic Competitive Intelligence at Industrial Scale

A publicly-traded global equipment manufacturer transformed competitor intelligence from a 100-hour-per-month manual research process tracking 50–100 rivals into an agentic system monitoring 200 competitors across 10,000+ sources per cycle.

Client
Palfinger AG
Industry
Headline result
$105,000/yr
$105,000/yr
Analyst Cost Redeployed
100 hrs/mo
Manual Research Replaced
200
Competitors Monitored
10,000
Sources Processed Per Cycle
The Problem

Manual competitive research couldn't cover the universe the business operates in.

A global industrial manufacturer in the aerial work platforms market needed to track 200 competitors across launches, pricing, and positioning. The work was manual — analysts scanning websites, reading publications, emailing summaries to stakeholders. It consumed 100 hours per month, ran weeks behind, and could realistically cover only 50–100 of the 200 competitors that mattered. Coverage was sampled, not systematic. Humans couldn't execute it at the scale the business operates.

The Solution

An end-to-end intelligence system built inside the company's existing stack.

CustomAI Studio built an end-to-end intelligence system inside the company's existing stack — no new tools for the people consuming it. Competitor sites, news feeds, and industry publications feed an event capture layer that classifies and routes content into a multi-method extraction harness processing 10,000+ sources per cycle across all 200 competitors. Structured data lands in SQL for reporting and a vector store for retrieval, with telemetry tracking source reliability and freshness.

Two workflow modules sit on top: a synthesis module that generates intelligence newsletters and pushes them to stakeholders, and a query module — exposed as an internal chatbot — that lets leadership ask natural-language questions of the full competitive history on demand.

The Result

Coverage moved from sampled to comprehensive — every competitor, every cycle, with real-time intelligence.

The universe expanded from 50–100 names the team could scan to all 200, with depth per competitor growing from a handful of sources to roughly 50. Intelligence latency collapsed from weeks-behind to same-day. Stakeholders stopped chasing analysts and started querying the system directly.

The 100 hours per month spent on surface-level scanning was redirected to deeper strategic work — roughly $105,000 per year in analyst capacity unlocked. For the first time, the business had real-time competitive coverage that scaled with the market — without scaling the team.

Under the hood.

The end-to-end system behind the Palfinger competitive intelligence engine — from event capture across competitor sites, news feeds, and industry publications, through a multi-method extraction harness processing 10,000+ sources per cycle, into SQL and a vector store, and out through a synthesis module that ships intelligence newsletters and a query module exposed as an internal chatbot.

01 INPUTS Scouting keywords Curated by team Scouting sources Homepages · blogs · journals 02 INGESTION · MONTHLY Scraping Pulls relevant sources Company homepages · blogs journals · industry feeds PDF extraction Tables · figures · text Data extraction Structured fields · metadata 03 STORE · CRITICAL PATH Vector Database RAG-indexed · cloud-hosted · single source for both delivery surfaces Market news · announcements · features · products · technology trends 04 NEWSLETTER · MONTHLY 04a Evaluate updates Since last newsletter 04b Compute diff Input + database changes 04c · AGENT Write scouting report Newsletter agent · drafts the issue 04d Mail communication Sent to subscriber list 04e · TERMINAL Stakeholders READS 05 CHATBOT · ON-DEMAND 05a · SOURCE Stakeholder query Ad hoc chat interaction 05b · AGENT Chatbot agent Retrieves · synthesizes · responds 05c Conversational output In-context answer 05d · TERMINAL Same stakeholder READS

Results.

  • $105,000/yr — Analyst capacity unlocked and redeployed to deeper strategic work
  • 100 hrs/mo — Manual competitive research replaced with an agentic system
  • 200 — Competitors monitored every cycle — up from 50–100 sampled by hand
  • 10,000+ — Sources processed per cycle across the full competitor set
  • Same-day — Intelligence latency, down from weeks-behind

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