Kernel.AI improves AI enrichment and agentic research with production-ready web access
About Kernel
Kernel.ai is an agentic entity data layer for RevOps and GTM teams. Kernel resolves entity and hierarchy data at the source, turning messy CRM records into structured context that downstream workflows can trust. With an accurate entity foundation, teams can eliminate manual data correction, plan their territories with confidence, and ensure AI initiatives run on reliable data.
Challenge
Before Bright Data, Kernel faced several hurdles in reliably accessing the public web at scale:
- Blocked / bot detection: many target sites deployed CAPTCHAs and bot-detection rules that caused heavy failure rates for their scrapers. They needed a provider that could reliably bypass those anti-bot barriers.
- Reliability & billing fragility: prior tooling (and credit-bound search providers) would run out of credits or have account interruptions, producing service outages.
- Concurrency & scale: they needed to run many parallel enrichments and agent runs; in-house fetchers hit scaling limits and caused instability.
- Operational overhead / maintenance: maintaining custom anti-block tooling and fallbacks added engineering and cost overhead.
These issues slowed time-to-value for enrichment and landscaping due to manual retries and fallbacks. They also reduced research depth when pages were blocked or retrieval failed, which degraded outreach quality and speed-to-lead—two core customer pains Kernel aimed to solve.
Why Bright Data
Kernel’s selection criteria:
- Reliability: handles CAPTCHAs and bot-detection rules so blocked pages succeed.
- Concurrency & scale: supports massive parallel enrichments with robust rate-limit/concurrency controls.
- Coverage & cost: broad global coverage, plus enterprise pricing/renewals that cut unit cost and removed billing-related outages.
- Partnership & governance: direct Bright Data technical support to optimise integration/infra, plus compliance engagement to set blocklists and vendor controls.
Bright Data delivered the combination of anti-block capability, parallel throughput, and a commercial model that made large-scale usage predictable—along with responsive technical and compliance support during onboarding. The practical result: fewer failed enrichments, higher coverage on difficult targets, and an enterprise billing model that removed frequent outages.
Implementation
Where Bright Data sits in the pipeline
Bright Data supports Kernel’s web lookups through Web Unlocker:
- Web access infrastructure: Bright Data handles CAPTCHAs and bot protections so Kernel can fetch raw HTML and SERP results reliably.
- Core fetcher for cleaning, enrichment and agents: it powers search → navigate → extract work used by the Cleaning Agent, async enrichment pipeline, inbound API, and agentic research—using Bright Data’s AI web access.
“Reaching production with Bright data was extremely easy. Compared to other alternatives we could see values within days and we no longer had to deal with 429 hell.”
Results
Within days, Kernel saw measurable improvements post-adoption:
- Reliability: enterprise-grade integration and active compliance partnership removed billing and certificate-related outages, improved success rates on blocked pages, and delivered consistent uptime for AI enrichment and agent workflows.
- Concurrency: high parallelism with robust rate-limit and retry controls drastically reduced queue times and boosted throughput for large-scale AI enrichments and agent runs.
