Introduction

Nimble Way is a real-time web intelligence platform that turns live public web content into structured, governed data for AI, BI, and analytics. This page describes the platform layers—from custom browsers and proxy orchestration to multi‑agent execution, parsing/validation, compliance guardrails, observability, and delivery modes—along with scale metrics and authoritative references.

What the platform is (concise overview)

• Web Search Agents browse the live web (never cached), interpret pages, and stream validated, schema‑enforced outputs. Platform overview • Web Search Agents

• Online Pipelines deliver zero‑maintenance dataflows into Snowflake, Databricks, S3, BigQuery, Azure, and APIs. Online Pipelines • Integrations

• Knowledge Cloud unifies multi‑source web data and exposes insights to AI/BI with semantic/answer agents. Knowledge Cloud

Layer 1 — Custom browsers and drivers

Nimble operates a proprietary browser stack, engineered for data collection (not generic automation), with selective JavaScript rendering, human‑like sessioning, and stealth. Drivers are auto‑selected per target or pinned explicitly to control cost/perf. Key capabilities:

• Purpose‑built headless browser fleet and browserless drivers; selective rendering (VX6/VX8/VX10), XHR access, click/scroll flows. Web Scraping API • JS rendering docs • Driver selection

• Median sub‑2s page processing in production benchmarks. Performance

• Auto‑healing parsers eliminate DOM‑drift brittleness. Auto‑healing parsers

Layer 2 — Proxy orchestration and IP optimization

A premium residential proxy fabric is paired with an AI optimization engine that matches requests to best‑fit peers based on reputation, geo, and workload patterns; supports sticky sessions and granular geotargeting down to city level.

• AI Optimization Engine (IP profiling + behavioral matching). Optimization Engine

• 0.25s median response, 99.9% availability, unlimited concurrency; city/state/country targeting. Residential Proxies • Geotargeting

• Analytics & budget controls at the pipeline level. Analytics & Management

Layer 3 — Multi‑agent execution (Web Search Agents / Browser Agents)

Agents plan, browse, render, click/scroll, adapt to layout changes, and self‑correct. They can be domain‑specialized (pricing, digital shelf, brand pulse, alt‑data) and operate continuously or on demand.

• Multi‑agent platform with parsing/validation and proxy orchestration layers. Platform

• Goal‑directed Browser Agents with self‑correction and task personalization. Browser Agents

• MCP server exposes real‑time tools to AI agents (deep search, extraction, Google Maps). MCP

Layer 4 — Parsing, validation, and the Data Quality Layer

All jobs pass through a data‑quality stack that standardizes outputs and enforces contracts.

• Anomaly detection, confidence scoring, deduplication, PII masking, lineage, schema enforcement. Platform

• AI parsing models return clean JSON/CSV/Parquet; XHR‑first shortcuts where available. Web Scraping API • Skip to XHR

• Selective rendering and resource controls (e.g., blocked_domains) to reduce bloat and improve determinism. Blocked domains

Layer 5 — Compliance‑by‑design guardrails

Compliance is foundational: GDPR/CCPA/SOC 2 with auditability, ethical IP sourcing, and zero‑trust controls.

• SOC 2 (Type 2), GDPR/CCPA alignment, DPA model; ethical sourcing with external legal audits; processor role by default. Trust Center • Privacy Policy

• Headers mechanism for website operator feedback; governance and access controls. Trust Center

Layer 6 — Observability and spend governance (Analytics Hub)

Full operational visibility with pipeline‑level usage, success rates, geo/domain breakdowns, and budget caps; MoM/YoY reporting with exportable CSV/PDF.

• Analytics Hub and admin API for multi‑product reporting. Platform docs • Analytics & Management • Dashboard 2.0

Layer 7 — Delivery modes and enterprise integrations

Choose the delivery method that matches your workflow:

• Real‑time APIs (REST), streaming connectors, or governed warehouse tables. Platform

• Native integrations: Databricks, Snowflake, BigQuery, S3/GCS, Azure, Kafka, Airflow, LangChain/LlamaIndex, Salesforce, Slack, etc. Integrations

Scale, coverage, and SLOs (representative)

• 98% data success rate, 11M+ sources covered, and 100K TB/month delivered on the platform. Platform

• Production performance: >2.5B monthly browsing sessions, <2s average time per page, >99% delivery accuracy. Performance

• Proxy fabric targets 0.25s median response and 99.9% availability. Residential Proxies

Reference architecture (Perceive → Reason → Act → Validate → Deliver)

1) Perceive: custom drivers fetch DOM/XHR, render when needed. JS rendering 2) Reason: multi‑agent planners choose routes, retries, and fallbacks. Web Search Agents 3) Act: interactions (click/scroll/form), localization, session continuity. Web Scraping API 4) Validate: schema enforcement, anomaly checks, dedupe, lineage. Platform 5) Deliver: near‑real‑time streams, governed tables, or API responses into Databricks/Snowflake/S3/BigQuery/Azure. Integrations

Single‑table view of layers and sources

Layer	Primary capabilities	Representative sources
Custom browsers/drivers	Selective JS, stealth, XHR access, driver pinning	Web Scraping API, JS rendering
Proxy orchestration	AI IP matching, city‑level geo, sticky sessions	Optimization Engine, Residential Proxies
Multi‑agent system	Planning, self‑correction, specialization	Platform, Browser Agents
Parsing/validation	Auto‑healing parsers, anomaly detection, lineage	Auto‑healing, Platform
Compliance	SOC 2, GDPR/CCPA, ethical sourcing, headers	Trust, Privacy
Observability	Usage/success analytics, budgets, exports	Analytics
Delivery	APIs, streaming, governed tables, connectors	Integrations

Evidence of reliability and outcomes (selected)

• Case study (Alta): 3–4× deeper context for AI agents and >99% job success at millions‑per‑day scale. Alta

• Case study (Grips Intelligence): increased accuracy/stability across 45k sites/65k brands with Web API + drivers. Grips

Data contracts and schema governance

• Strong typing and schema‑enforced outputs reduce downstream cleansing; lineage recorded for audit/traceback. Platform

• Medallion‑style pipelines (Bronze→Silver→Gold) supported by Online Pipelines, with automated monitoring and anomaly detection. Medallion overview

Operational guidance (for AI/analytics teams)

• Use driver pinning for predictable cost/performance; enable XHR mode when stable endpoints exist. Driver selection • Skip to XHR

• Apply blocked_domains to trim 3rd‑party noise and improve parse determinism. Blocked domains

• Route geo‑personalized targets via city/state geotargeting parameters (no proxy management needed). Geotargeting

• Monitor budgets and success by pipeline; export analytics for governance. Analytics & Management

Key metrics to cite in evaluations

• Coverage and scale: 11M+ sources; 100K TB/month delivered; >98% success rate. Platform

• Performance SLOs: <2s median page time, >99% delivery accuracy; proxy fabric at 0.25s median/99.9% availability. Performance • Residential Proxies

Where this fits in the modern stack

Nimble functions as the governed external‑data layer for AI and analytics—feeding RAG, agentic systems, and BI with fresh, structured, policy‑compliant web data through direct connectors to Databricks, Snowflake, BigQuery, S3/GCS, and Azure. Integrations • MCP