Service Type: content data

Knowledge & AI Data Preparation

The foundation every AI needs to answer well

Key Features

IQ quality scoring

Every knowledge source gets an automated quality score covering completeness, clarity, and retrieval confidence — so you see AI readiness before going live.

Multi-source ingestion

Ingest PDFs, help center URLs, product catalogs, internal wikis, CMS exports, and structured databases through a single pipeline.

Semantic chunking & enrichment

Hierarchical chunking and AI enrichment ensure content is split and indexed at the right granularity for precise retrieval.

Continuous sync

Live content sources re-ingest automatically when content changes — no manual rebuilds when you update a product description or policy.

Gap detection

IQ analysis maps content coverage against your actual support query patterns, surfacing the gaps that cause the most wrong or hedged answers.

AI is only as good as the knowledge it can reach. Most teams discover this the hard way: they launch a chatbot, it gives wrong answers, and trust evaporates fast.

The problem is rarely the AI model. It's the content underneath — scattered across help docs, outdated PDFs, inconsistent product data, and internal wikis that no one maintains. Without structure and quality scoring, every AI system will hallucinate, hedge, or fail at the exact moment a customer needs a clear answer.

Reaktly's Knowledge & AI Data Preparation service fixes the foundation. We centralize your content, assess it against Reaktly IQ quality criteria, restructure it for retrieval, and establish ongoing sync pipelines so your knowledge stays current. The outcome is measurably better AI accuracy, faster time to trust, and a knowledge base your whole team — human and AI — can rely on.

Delivery Timeline

1

Knowledge Audit & Gap Analysis

Week 1

We inventory all content sources your AI should know about — help centers, product catalogs, policy documents, internal wikis, support ticket archives — and run an IQ scoring audit to identify gaps, contradictions, and low-quality coverage before any ingestion begins.

  • Map all content sources: URLs, PDFs, databases, CMS exports
  • Run IQ quality assessment across a sample of existing content
  • Identify high-priority gaps aligned to top support query categories
  • Agree on source priority and ingestion order
2

Ingestion, Structuring & Embedding

Weeks 2–3

We ingest your content through the Reaktly IQ pipeline — chunking, enriching, generating embeddings, and applying reranking to maximize retrieval precision. Each source gets an IQ quality score so you can see exactly where your AI foundation is strong and where it needs reinforcement.

  • Ingest and parse content: PDFs, markdown, URLs, product feeds, structured data
  • Apply hierarchical chunking and semantic enrichment
  • Generate and index high-quality embeddings with reranking
  • Assign IQ scores per source and surface low-quality items for review
  • Configure continuous sync for live content sources
3

Quality Review & Handover

Week 4

We review IQ scores with your team, resolve critical gaps, and hand over a documented knowledge architecture with a prioritized improvement backlog. You leave with a clear view of what your AI knows, how confidently it knows it, and what to work on next.

  • Review IQ score report and triage low-scoring sources
  • Resolve critical gaps or contradictions with your content team
  • Document knowledge architecture and source ownership
  • Hand over improvement backlog and sync maintenance playbook

What You Get

  • Structured IQ knowledge baseAll priority content ingested, chunked, embedded, and indexed — ready for accurate AI retrieval with source citations.
  • IQ quality score reportPer-source quality scores identifying coverage gaps, low-confidence content, and priority improvement areas.
  • Source coverage mapDocumentation of every knowledge source, its ingestion status, sync frequency, and assigned owner.
  • Continuous sync pipelineAutomated re-ingestion for live sources (CMS, product feeds, help center) so your knowledge stays current without manual intervention.
  • Improvement backlogPrioritized list of content gaps and quality issues, mapped to your top support query categories.

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