Build Custom Intelligence Engines That Work
While your competitors are still using basic web searches and manual research, the smartest B2B teams are already building custom intelligence engines that give them 6-12 month market advantages.
Fairway has architected 200+ custom intelligence engines across B2B categories and markets. We've cracked the code on turning scattered signals—GitHub repos, SEC filings, forums, press releases—into systematic competitive advantage.
The problem: Most companies are drowning in fragmented intelligence sources but have no systematic way to capture, process, and act on these signals. The companies that figure this out first will dominate their markets. The window is closing.
Developer Intelligence
Spot technology shifts 6 months before competitors
Financial & Strategic Signals
Predict market moves from regulatory filings
Social & Community Intelligence
Capture sentiment shifts as they happen
Product & Competitor Tracking
Know about competitive moves before they're announced

The result: A systematic intelligence advantage that feeds directly into your ABM, RevOps, and strategic decision-making—while your competitors are still playing catch-up.
Standard Use Cases vs Fairway's Intelligence Specialization
Fairway has architected 200+ custom intelligence engines across B2B categories and markets.
Standard Custom Search Engine Uses
  • Site search for documentation
  • Basic product catalogs
  • Simple knowledge bases
  • General content discovery
  • Basic search boxes for websites
Fairway's B2B Intelligence Approach
  • Targeted intelligence funnels for ABM/RevOps
  • Multi-source data aggregation (GitHub + SEC + forums)
  • Programmatic feeds into Colab/Python pipelines
  • Signal detection and taxonomy mapping
  • Automated CSV/JSONL export for research workflows
  • Integration with business intelligence platforms

Outcome: We don't just implement search—we architect intelligence systems that feed your business strategy. With 200+ engines deployed, we've refined the playbook while others are still figuring out basic search boxes. The intelligence gap is widening.
The Fairway Intelligence Architecture
Fragmented Data Sources
We aggregate disparate data points from across the digital landscape, including GitHub repositories, SEC filings, industry forums, and press releases. This forms the foundational layer of our intelligence.
Fairway's Processing Layer
Our proprietary engine transforms raw data into structured insights through advanced signal detection, robust taxonomy mapping, and intelligent data enrichment algorithms, ensuring data relevance and accuracy.
Strategic Intelligence
This refined data yields critical strategic intelligence, encompassing precise trend analysis, in-depth competitive insights, and early market signal detection, tailored to your unique business objectives.
Business Impact
Translate intelligence into tangible results: accelerate pipeline growth, inform critical strategic decisions, and secure a decisive competitive advantage in your market. This is intelligence that drives ROI.
Getting Started in Four Steps (Intelligence Edition)
01
Name Your Engine
Organize by mission: "Developer Intent — Cloud Data Eng," "Financial Signals — SaaS," "Competitive Intel — Observability."
02
Define the Source Scope (URL Patterns)
Start tight, then expand: docs, forums, IR pages, EDGAR, issue trackers, status pages, etc. (Examples below.)
03
Configure Features
Add refinements for themes (Dev Releases, Security, Financials, Social). Add synonyms to normalize variations (e.g., "RTO" ↔ "return to office," "price increase" ↔ "pricing change"). Enable sort by date (if supported) + date restrict for freshness sweeps.
04
Implement & Automate
Use the JSON API for server/Colab pipelines (preferred for intel). Optionally embed the search UI on an internal page for manual discovery. Schedule Colab jobs to write timestamped CSV/JSONL bundles to storage.
Mastering URL Patterns (with Intel-Friendly Examples)
Patterns (case-sensitive; up to ~5,000 per engine):
Developer docs & changelogs:
  • docs.example.com/*
  • www.example.com/changelog/*
  • developer.example.com/*
GitHub (issues/releases for specific orgs):
  • github.com/example/*/releases*
  • github.com/example/*/issues*
Stack Overflow / Q&A:
  • stackoverflow.com/questions/*
Product communities:
  • community.example.com/*
  • discuss.example.org/*
Security & status:
  • status.example.com/*
  • www.example.com/security/*
  • nvd.nist.gov/vuln/detail/*
Financial filings & IR:
  • www.sec.gov/Archives/edgar/data/*
  • investors.example.com/*
  • www.example.com/investors/*
Social (public, author-friendly paths):
  • linkedin.com/company/*/posts/*
  • linkedin.com/posts/*
  • reddit.com/r/*/comments/*
Inclusions: docs, blogs, /releases, /changelog, /security, /investors, /press, /kb, /support, /status, /community, SEC archives.
Exclusions: /login/, /sales/, /cart/, /ads/, test/staging subpaths, pagination traps, user-generated noise you don't trust.
The Reality: This Requires Dedicated Investment
Achieving truly effective intelligence ingestion is far from a free endeavor; it demands significant and dedicated investment in both financial resources and human capital. This isn't a task for half-measures or relying solely on a basic, limited free tier.
  • Escalating Costs: Google's pricing structure means $500 for every 100,000 signals. When you're pulling serious B2B intelligence data, a single comprehensive data pull can easily generate 100,000+ signals across multiple sources (GitHub repos, SEC filings, forums, press releases). That's $500+ per intelligence sweep - and you need regular sweeps to stay current.
  • Dedicated Teams: Building, customizing, and continuously maintaining these sophisticated intelligence systems requires specialized expertise. You will need dedicated teams of engineers, data scientists, and analysts to ensure optimal performance and relevance.
  • Competitive Disadvantage: Without a properly architected workflow and consistent investment in your intelligence infrastructure, you risk being outmaneuvered. Competitors who commit to these systems will inevitably gain a significant advantage in market insight and strategic decision-making.
  • Underestimated Complexity: Most companies significantly underestimate the technical complexity involved in setting up, integrating, and maintaining these systems, as well as the ongoing operational costs. This is not a set-it-and-forget-it solution.
The choice is clear: either commit fully to a robust investment strategy to build a high-performance intelligence capability, or accept that your organization will be outpaced by those who do.
Managing Your Intelligence Sources
Once your intelligence engine is running, you need ongoing management to keep it effective. The control interface gives you four key areas to monitor and adjust your data collection.
Source Management
Add/remove data sources, track what domains you're monitoring
Query Optimization
Fine-tune how you search and filter information
Display Settings
Control how results look (only needed if people will see the interface)
Performance Monitoring
Track usage and see which sources give you the best intelligence
Partner with Fairway for Custom Intelligence Feeds
Why build this complex infrastructure yourself? Fairway specializes in architecting custom intelligence data feeds tailored to your specific market segments. Whether you need intelligence on 1-5 key segments or comprehensive coverage across 25-50 market areas, we've already solved the technical complexity, cost optimization, and ongoing management challenges.
With 200+ intelligence engines deployed, we know exactly how to extract maximum value while controlling costs. Let us build your custom intelligence infrastructure so you can focus on acting on the insights, not managing the data pipelines.
Get Your Custom Intelligence Feed