Better Company Intelligence Starts With Better Data
afterSpark continuously evaluates and normalizes billions of data points, turning fragmented and changing information into trusted, actionable intelligence.
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Data Doesn't Always Agree
Data is constantly changing. It's collected at different times, from different sources, using different standards and methods.
As the world changes, information can become fragmented, inconsistent, outdated, or incomplete. One source may say one thing while another says something different.
More data doesn't necessarily solve the problem.
The challenge isn't finding more data. It's determining what to trust.
- Source A: Acme Inc.; Software; 51–200 employees; San Jose, CA
- Source B: Acme Technologies; IT Services; 201–500 employees; Austin, TX
- Source C: acme.com; SaaS; 150 employees; San Jose, CA
afterSpark Intelligence Engine: Evaluate → Normalize → Validate → Maintain
Normalized record: Acme Inc.; Software; NAICS 541511; 101–250 employees; $10M–$50M revenue; San Jose, CA; acme.com
Turning Conflicting Signals Into Trusted Intelligence
afterSpark continuously evaluates data for completeness, freshness, consistency, and change.
Conflicting signals are evaluated, information is normalized, and the most reliable representation emerges from the available evidence.
Proven Data Methods, Enhanced by AI
AI is part of the afterSpark Intelligence Engine. It isn't the source of truth.
afterSpark combines proprietary data, deterministic methods, pattern matching, machine learning, and AI to evaluate and maintain intelligence.
- Proprietary Data: Provides the signals and foundation for afterSpark intelligence.
- Deterministic Processes: Apply consistent rules and standards across data.
- Pattern Matching + Machine Learning: Identify relationships, inconsistencies, patterns, and changes across data.
- AI: Helps interpret varied signals, resolve ambiguity, and address complex edge cases.
Normalized by Design
Accurate Data Is Only Useful When It Means the Same Thing Everywhere
Data can be technically correct and still be difficult to use.
Different sources use different names, classifications, formats, ranges, and standards. afterSpark normalizes those signals into consistent structures so data can be used reliably across systems, workflows, applications, analytics, and AI.
Standardized Industry Classification
afterSpark uses established classification systems including NAICS and SIC to create a consistent foundation for understanding what a company does.
That standardized foundation can then be translated into the classifications used by marketing platforms, CRMs, advertising platforms, and other business systems.
One normalized foundation. More ways to put it to work.
Data Never Stops Changing
Data shouldn't be treated as something that's finished.
New information appears. Existing information becomes outdated. Relationships change. Companies grow, shrink, move, rebrand, merge, restructure, and disappear.
afterSpark continuously reevaluates information as new signals emerge, helping keep intelligence accurate and actionable as the world changes.
One Intelligence Layer. Built to Be Used.
The afterSpark Intelligence Engine provides a shared foundation for evaluating, normalizing, and maintaining intelligence across the products and experiences we build.
- Audience Builder: Turn an ICP into a targeted company audience using normalized industry, geography, employee size, revenue, and other company intelligence.
- APIs: Bring trusted, normalized intelligence directly into your applications, workflows, products, and systems.
- Chrome Extension: Access company intelligence while you browse, research accounts, build audiences, and prospect.
- AI & Agents: Give AI systems structured intelligence so they can work with reliable business facts instead of guessing.
One intelligence layer. Multiple ways to put it to work.
Better Data Powers Better Outcomes
Trusted, normalized intelligence
- Targeting & Audiences: Find the right companies
- Enrichment: Improve existing records
- Analytics: Analyze consistently
- Automation: Act with confidence
- AI & Agents: Work from reliable facts
Better inputs. More reliable outputs.
Put Better Intelligence to Work
Whether you're building an audience, enriching a workflow, developing an application, analyzing data, or giving an AI agent access to reliable information, better outcomes start with better data.
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