Knowledge Layer of Intelligence Engineering

One Engine. Every Context.

Knowledge Stack is Infozense's single product — a Context Engine that stores, retrieves, and governs knowledge for any domain. Each application brings its own brain. Knowledge Stack is the shared memory.

See the Architecture See Applications
Sub-second*
Search latency
Billions*
Documents at scale
Multilingual
TH + EN + more

* Performance depends on architecture, data volume, and infrastructure configuration.

Foundations

Why Knowledge Engineering

Knowledge Engineering is the discipline of capturing, storing, retrieving, reasoning over, and governing knowledge. It has over 40 years of foundations in AI research. A Knowledge-Based System (KBS) has a classical architecture: a knowledge base, an inference engine, and an interface. Knowledge Stack is a modern KBS — that same proven architecture built on modern components: search engines, vector databases, analytics engines, and LLM-based agents. The knowledge base and tools are universal and shared. The reasoning and interface are per-application. One engine. Many contexts.

Architecture

Four Layers. One Clear Boundary.

Knowledge Stack is Infozense's single product — one Context Engine, applied to many domains.

Per-Application — each domain brings its own
L4

Application Layer

UIs, dashboards, chat, embeds
L3

Agent Layer

LLM reasoning, answer composition (pluggable)
shared boundary
Knowledge Base / Context Engine — universal, shared Provided by INFOZENSE
L2

Tool Layer

search, retrieve, query; tenancy, governance
L1

Data Layer

Search & vector engine, analytics engine, shared catalog
Capabilities

Ten Capabilities Across Four Layers

Every capability maps to a layer in the architecture. The Context Engine (L1+L2) is shared; reasoning and interface (L3+L4) are per-application.

Hybrid Search

L1/L2

Full-text keyword search and semantic vector search in a single query. Find documents by exact terms or by meaning — whichever gets the best result.

Document Intelligence

L2

Automatically parse PDFs, Office documents, and scanned images. Extract text, tables, and structure — ready for search and retrieval without manual effort.

RAG (Retrieval-Augmented Generation)

L3

The agent layer retrieves documents from the Knowledge Base and composes grounded answers with citations. Each domain application configures its own RAG prompts and LLM.

Real-Time Analytics

L1/L2

Track usage patterns, identify knowledge gaps, and monitor search quality metrics. Understand what your teams are looking for — and what they cannot find.

Knowledge Governance

L1/L2

Role-based access control, document lifecycle management, and complete audit trails. Know who accessed what, when, and ensure sensitive content stays protected.

Workflow Orchestration

L2/L3

Approval chains, content review processes, and scheduled re-checks. Automate the lifecycle of knowledge from creation through retirement.

Multilingual

L1

Native Thai and English search and retrieval — with support for additional languages. Ask in Thai, find English documents — and vice versa. Built for Southeast Asian enterprise use.

Quality Monitoring

L2

Measure retrieval precision, content freshness, and knowledge coverage. Detect gaps and stale documents automatically — so quality improves over time.

Scalable Vector Search

L1

Start with built-in vector search for millions of documents. Scale to a dedicated vector database for billions — without changing your application.

Knowledge Graph

L1 Roadmap

Extract entities and relationships to build a knowledge graph — then reason across connections. Answer multi-hop questions like "How do these regulations interact?" instead of just "What does this document say?"

Domain Contexts

One Engine, Many Contexts

Customers buy one engine and load their own contexts. Each row below is a domain application running on Knowledge Stack.

Domain Context Example Assets
Market intelligence Filings, factor tables, news
Supply chain POs, shipments, supplier catalogs, contracts See supply chain application →
IoT Sensor manuals, device specs, telemetry See IoT application →
Geospatial Cadastral records, GIS layers, satellite See geospatial application →
Skills / HR Job descriptions, resumes, training material See skills application →
Healthcare Drug databases, clinical guidelines
Regulatory Laws, circulars, rulings

What stays the same

Engines, tool contract, schemas, tenancy, governance.

What changes per context

Registered assets, reference agent prompts, UI style.

The Analogy

Memory vs Thinking

Knowledge Stack is the shared memory system

It stores, indexes, retrieves, and governs knowledge. It does not answer questions or generate content.

Each domain application brings its own brain

The agent and LLM do the reasoning. Many brains share one memory.

That is why Infozense can apply Knowledge Stack to new domains quickly — the engine is already there. Only the context changes.

Run It Your Way

We Engineer the Intelligence. You Choose Where It Runs.

Every engagement starts with consulting — we understand your knowledge challenge and design the right solution. Then you choose how to run it.

INFOZENSE Managed

Coming Soon

We host, operate, and optimize it for you.

  • Monthly subscription — predictable costs
  • Auto-scaling, updates, and monitoring
  • Go live in days, not months

Best for: teams that want results without managing infrastructure.

Customer Operated

Your cloud or on-premise. Full control over data and security.

  • AWS, GCP, Azure, IBM Cloud, INET, or on-prem
  • We train your team to operate and scale
  • Ongoing support retainer available

Best for: regulated industries and data sovereignty requirements.

Not sure which is right? That's what the consulting phase is for. We'll recommend the best fit.

Book a Consultation
How We Deliver

The INFOZENSE Method

The same proven methodology that powers all our engagements — consulting first, then technology that delivers.

1

Assess

Audit your knowledge landscape and identify the highest-value use case

Strategic Consulting →
2

Build

Configure Knowledge Stack, ingest your documents, build search and retrieval pipelines

Solution Development →
3

Measure

Track search quality, retrieval accuracy, and knowledge utilization metrics

Performance Analytics →
4

Scale

Expand to new document sources, add domain contexts, grow continuously

Operational Excellence →
Get Started

Ready to Deploy Your Context Engine?

Tell us about your knowledge challenge — scattered documents, poor search, no governance. We'll assess the fit and show you how Knowledge Stack provides the shared memory your applications need.

Book a Consultation

We welcome international engagements — serving clients across Southeast Asia and beyond.