Content Intelligence and Personalization

Content Intelligence & Personalization

Help content managers and business leaders turn operations into a competitive edge with AI-driven processing, semantic understanding, and scalable distribution, saving time and effort.

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The Content Velocity Challenge

Organizations across media, eCommerce, publishing, marketing, and genealogy face manual processes, fragmented data, and missed real-time opportunities.

Financial News Automation

Manual processing of earnings reports (45-60 min). Analyst burnout. Missed publishing windows. Inconsistent quality.

eCommerce Syndication

Content fragmented across CMS, S3, SharePoint, ERPs. 23 languages. Real-time traffic data integration missing.

Consumer Insights

Multi-platform sentiment analysis. Multi-lingual, multimodal content. Data scattered, insights delayed.

Why Content AI Projects Fail: The Data Reality

60%
Content fragmented

Product content scattered across legacy systems with no unified schema

75%
No unified query

Different APIs block semantic matching.

80%
Missing semantic layer

ML models cannot understand fragmented data relationships.

90%
No streaming infra

Real-time syndication requires integrated context.

Our integration-first approach: build data foundation on existing platforms. Layer 0 uses iBEAM to reduce 12-18 months to 90 days.

Reusable Foundations

Integrated foundations service multiple applications, reducing time-to-value while maximizing reusability.

Traditional

Traditional Problem

Each content challenge handled as a separate project with months of work and no shared infrastructure.

Our approach

Our approach

Build unified foundation serving processing, syndication, insights, and more. Deploy first capability in 12-16 weeks, then expand rapidly.

Powered by our AI Foundry

Our AI agent orchestration platform with 50+ pre-built agents demonstrates proven effectiveness, inspiring confidence in your team. Accelerated deployment means your team sees results quickly.

Accelerated with iBEAM: Data preparation foundation reduced from 12-18 months to 90 days, with 75% effort reduction.

1

Data Foundation

Content lakes • Semantic indexing • Streaming pipelines • Data quality • Unified metadata

→ Ensures AI-ready content
2

Content Processing Engine

Parsing (OCR, NER) • Multi-format • Entity extraction • Validation • Handwriting recognition

→ Extracts structured intelligence
3

Semantic Analysis

Vector embeddings • Summarization • Topic extraction • Sentiment analysis • Cross-document search

→ Generates actionable insights
4

Personalization & Distribution

Recommendation engines • Multichannel syndication • SEO optimization • Dynamic content adaptation

→ Delivers tailored content at scale
5

Operations & Governance

Workflow automation • Compliance monitoring • Audit trails • Governance frameworks • Continuous learning • Analytics

→ Manages workflows, ensures compliance, enables continuous improvement

OUR RECENT WORKS View all

Financial News Publishers

9x Faster

Faster Content Production

Extracts earnings data instantly instead of 45+ minutes, processing 1,000+ daily reports with 97% precision for real-time coverage.

Learn More →
Retail

3x Coverage

Product Content Validation

Reduced QA from days to 5 seconds per product, increasing coverage by 3x and reducing manual QA efforts by 50% across 1,900+ retailer sites.

Learn More →

Additional Content Intelligence Applications

The same foundations adapts to these and many other content challenges:

Historical Document Processing & Record Linking (Genealogy)

Content Personalization & Dynamic Recommendations

Digital Publishing Operations & Workflow Automation

Marketing Content Optimization & Performance Analytics

Multi-Channel Content Distribution Management

Automated Content Categorization & Metadata Tagging

Content Compliance & Governance Automation

AMulti-Language Content Operations

Implementation Timeline


Data Foundation

Weeks 1-4

Integrate content sources, normalize schemas, deploy vector embeddings.

Processing Engine

Weeks 5-8

OCR, NER, and entity extraction pipelines implemented and tested.

Semantic Layer

Weeks 9-12

Topic modeling, summarization, cross-content search deployed.

Personalization & Distribution

Weeks 13-16

Recommendation, multichannel syndication, and real-time adaptation live.

Get Started

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