AI Services

AI Knowledge Graph Search Engine

Deep semantic search across structured + unstructured corporate knowledge: auto-builds a navigable knowledge graph from Confluence, Slack, Drive, Jira, and CRM; facet navigation, path-finding between related entities, and answer synthesis with cited sources.

Features

  • Auto-ingest: Confluence, Slack, Drive, Jira, Notion, SharePoint
  • Auto-built navigable knowledge graph with entity recognition
  • Faceted navigation + path finder (A→B shortest path through relations)
  • Answer synthesis with inline citations + source confidence scores
  • On-prem AIR-gapped deployment option for public-sector / PHI

Pricing

basic249
pro849
enterpriseCustom

Get Started

Ready to get started? Contact us for a custom quote.

Benefits

Answer how-do-I type queries in seconds that previously took hours of searching
Eliminate 40-70% of repeated support tickets by surfacing canonical answers
Build a living knowledge graph without manual taxonomy work

ROI Calculator

Estimate the business value of AI Knowledge Graph Search Engine for your organization.

$5,000/ month
Monthlyest. return
$16,000
Payback period
6 months
Year 1 net gain
$132,000

Estimates based on 3.2x average productivity lift for ai category services. Actual results vary by workflow maturity, organisation size, and implementation depth.

Why AI Knowledge Graph Search Engine?

  • Pre-built by experts — no multi-month build cycle
  • Fully managed 24/7 — zero DevSecOps burden
  • Unlimited proposals, custom pricing & SLAs
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Deployment Roadmap

AI-Inferred • 5 phases

Estimated timeline for AI Knowledge Graph Search Engine — adapt to your team size and complexity.

1. Scope & Data Audit

Week 1–2
  • Define use-cases + success KPIs
  • Inventory existing data sources + formats
  • Data quality + labelling review
  • Tech-stack + model-selection workshop

2. Model & Pipeline Build

Week 3–5
  • Fine-tune / prompt-engineer model
  • Build inference pipeline + API
  • Unit tests + eval on hold-out set
  • Internal demo + feedback loop

3. Pilot & Evaluation

Week 6–7
  • Pilot with 10–20 real use-cases
  • Collect user feedback + KPI report
  • Fix edge-cases + regressions
  • Finalize production config

4. Production Roll-out

Week 8
  • CI/CD pipeline + rollback plan
  • User training + documentation
  • Go-live monitoring + alert setup
  • 30-day health-check call

5. Optimize & Scale

Ongoing
  • Monthly quality review
  • Model fine-tune on new data
  • Usage analytics + cost optimisation
  • Feature backlog prioritisation

Ready to Get Started?

Let's discuss how AI Knowledge Graph Search Engine can transform your business. 364 E Main St STE 1008, Middletown, DE 19709 · +1 302 464 0950