Make your organisation understandable to AI.
Transform fragmented enterprise data into a unified, semantically coherent infrastructure designed for agentic intelligence.
1240
Data Sources
96
Systems
1.8M
Documents
23
Concepts
01The enterprise condition
Enterprises do not have a data shortage. They have a meaning problem.
Your organisation already holds decades of valuable information. It is spread across systems that were never designed to explain themselves to a machine.
Information already in the estate
Why agents fail on it
- 01fragmented
- 02poorly described
- 03duplicated
- 04inconsistent
- 05lacking common semantics
- 06disconnected from business processes
- 07disconnected from policies
- 08difficult to retrieve safely
- 09inaccessible without deep system knowledge
- 10lacking provenance
- 11lacking relationships
- 12not packaged for AI consumption
AI does not simply need access to data. It needs context, meaning, relationships, trust and permission.
02How it works
From raw information to machine-understandable intelligence.
One continuous pipeline: discovery, understanding, semantic structure, governance, packaging, and finally agents that act on business meaning.
Stage 01 · raw
Raw enterprise information
Stage 02 · sensemesh
SenseMesh
Stage 03 · graph
Enterprise Meaning Graph
Stage 04 · products
Agent-ready intelligence products
Stage 05 · agents
AI agents
Stage 06 · outcomes
Business outcomes
03Platform capabilities
Discover. Understand. Give it a semantic spine.
Three capabilities operate continuously across cloud, on-premise and hybrid estates, building a business semantic layer that is independent of source systems.
Automatically discover organisational information across cloud, on-premise and hybrid environments.
1 240
sources discovered
96
systems connected
1.8M
documents analysed
318
datasets indexed
Use AI to determine what organisational information actually means — not just where it lives.
Instead of
proc_policy_final_v7.pdf
SenseMesh understands
A business semantic layer independent of source systems. Agents interact with concepts, not implementation complexity.
maps to
04Flagship capability
The Enterprise Meaning Graph.
SenseMesh builds a continuously evolving graph of what your organisation is and how it works. This is more than a traditional knowledge graph: every node and every relationship carries the metadata an enterprise agent needs to be trusted.
The graph connects
Why it matters
Your AI agents should not have to rediscover what your organisation means every time they work. SenseMesh creates that understanding once and makes it reusable everywhere.
4.2M
nodes
31M
relationships
93%
provenance
05Agent-ready data products
Enterprise intelligence, packaged for consumption.
SenseMesh assembles reusable intelligence products from the Meaning Graph — versioned, governed and directly consumable by agents.
prd-cust-01
- Customer profile✓
- Interactions✓
- Products✓
- Transactions✓
- Complaints✓
- Documents✓
- Consent✓
- Risk indicators✓
- Policies✓
- Available actions✓
prd-supp-01
- Supplier profile✓
- Contracts✓
- Invoices✓
- Payments✓
- Performance✓
- Correspondence✓
- Risk✓
- Compliance✓
- Relevant policies✓
prd-empl-01
- Role✓
- Department✓
- Skills✓
- Permissions✓
- Activities✓
- Policies✓
- Tasks✓
- Training✓
- Authorisations✓
Exposed through
Agents should consume business meaning — not decipher 2 000 database tables.
06Agent opportunity discovery
SenseMesh tells you what intelligence you can build.
SenseMesh analyses the intelligence already available in your estate and scores concrete agent opportunities — with the data gaps, controls and value attached.
Invoice Reconciliation Agent
SAP · SharePoint · Email
est. annual value
R8.4m
96%
data readiness
High
business value
82%
automation
Medium
complexity
- business problem
- Finance reconciles supplier invoices against purchase orders and goods receipts manually across three systems, with 11 000 exceptions per year.
- data available
- Invoices, purchase orders, goods receipts, payment runs, supplier master
- missing data
- Structured dispute outcomes, 2019–2021 scanned remittances
- actions required
- Match, flag exception, request clarification, prepare payment proposal
- recommended human controls
- Human approval above R250 000 · dual authorisation on supplier changes
- Contract Compliance AgentR5.2m
Legal · ERP · Documents
71%Medium - Supplier Risk AgentR3.9m
Procurement · News · Registries
84%Low - Complaint Resolution AgentR4.6m
CRM · Telephony · Cases
77%Medium - Revenue Leakage AgentR9.8m
Billing · Contracts · Usage
68%High - Fraud Investigation AgentR12.1m
Core banking · Events · Alerts
88%High - Customer Retention AgentR5.7m
CRM · Service desk · Call logs
79%Medium - Employee Onboarding AgentR2.3m
HRIS · Identity · Training
91%Low - Policy Compliance AgentR3.1m
Policies · Processes · Audit
74%Medium - Procurement AgentR6.5m
SAP · Suppliers · Catalogues
81%Medium - Case Management AgentR4.2m
Cases · Documents · Workflow
72%Medium
SenseMesh does not only tell you what data you have. It tells you what intelligence you can build from it.
07Enterprise Intelligence Map
An interactive map of organisational intelligence.
Every domain, every number, drillable — from connected systems down to individual datasets, concepts and identified agent opportunities.
Customers domain
domain 01 / 0842
connected systems
318
datasets
1.8M
documents
23
recognised concepts
87%
semantic coverage
74%
agent readiness
12
AI opportunities
drill down by
08Agent readiness
Enterprise Agent Readiness.
A continuously recalculated score across seven dimensions, drillable by domain, department, system, dataset, use case and agent.
Enterprise Agent Readiness
8 domains · 180 systems · recalculated hourly
detected conflict
Customer addresses differ between CRM and ERP for 18 420 customers.
recommended master
CRM
confidence
93%
affected AI use cases
continuously scored
09Industry intelligence packs
Start with your industry's vocabulary, then extend it.
Configurable ontology and semantic packs give SenseMesh a head start on the concepts, relationships and regulatory classifications your sector already uses. Every pack is extendable by the customer.
- Customer
- Account
- Transaction
- Loan
- Facility
- Collateral
- KYC
- AML
- Risk
- Patient
- Practitioner
- Encounter
- Diagnosis
- Medication
- Treatment
- Claim
- Citizen
- Programme
- Application
- Case
- Service
- Grant
- Supplier
- Budget
- Payment
- Learner
- Programme
- Provider
- Facilitator
- Assessment
- Moderator
- Employer
- Funder
- Outcome
also available
10AI-first experience
SenseMesh is operated in natural language — and answers visually.
Ask the platform about your own organisation. Results come back as structured, drillable evidence rather than paragraphs of prose.
also asked
“Show me datasets containing customer identity information.”
“Create a customer ontology.”
“Show me datasets that have not changed for two years.”
“Which agents could deliver the highest value in 90 days?”
“Explain where our customer data comes from.”
Supplier ABC (Pty) Ltd · 6 systems · 412 documents
- contracts
- 4 active · 2 expired
- invoices
- 1 208 · R41.2m lifetime
- correspondence
- 318 emails · 12 call recordings
- risk
- 2 open findings · rating B
- governing policy
- Procurement Policy v4.2
11Lineage
“Where did this answer come from?”
Every agent answer traces back through the intelligence product, the Meaning Graph, the semantic mapping and the transformation to the originating record.
- 01→
Source system
SAP · BUT000
- 02→
Ingestion
batch + CDC · 04:15 daily
- 03→
Transformation
standardise · deduplicate · mask
- 04→
Semantic mapping
→ concept CUSTOMER
- 05→
Meaning Graph
node 4.2M · edges 31M
- 06→
Intelligence product
prd-cust-01
- 07→
AI agent
Collections Agent
- 08→
Business decision
payment arrangement offered
12Trust and governance
Permissions must propagate into agent retrieval and action.
Governance is not a layer bolted on afterwards. It is carried by every node, edge, product and retrieval path in SenseMesh.
controls
principle
An agent seeing a concept does not automatically mean it can see every underlying record.
Retrieval is filtered by identity, attribute, sensitivity and consent at query time — and every action an agent takes is attributed, logged and reversible.
13Multi-tenant enterprise architecture
Deploy it where your data is allowed to live.
Global platform administration is separated from tenant administration, and every tenant is isolated end to end.
SaaS
SenseMesh-operated multi-tenant
Private cloud
dedicated tenancy, our infrastructure
Customer cloud
your subscription, your region
Hybrid
control plane hosted, data plane local
On-premise
fully in-estate deployment
Sovereign
in-country, in-jurisdiction operation
isolated per tenant
From fragmented enterprise information to governed machine-understandable intelligence.
14Work with existing investments
Keep your data platform. Add understanding.
SenseMesh sits above what you already run. It does not ask you to migrate, replatform or abandon a warehouse, lakehouse or data mesh programme.
feeds any AI platform
Build organisational understanding once. Make it available to every authorised AI.
15Relationship to OneCortex
Two questions, two layers.
SenseMesh answers: what does the organisation know and what does it mean? OneCortex answers: what should intelligent workers do with that knowledge? SenseMesh also works independently with external agent ecosystems.
Enterprise Systems
ERP · CRM · documents · lakes · legacy
SenseMesh
discover · understand · semantic layer · meaning graph · govern
Agent-Ready Enterprise Intelligence
governed, contextual, reusable products
OneCortex
orchestration of intelligent workers
Agents + Digital Workers
customer · finance · risk · operations
Business Processes
automated, supervised, auditable
SenseMesh answers
What does the organisation know and what does it mean?
OneCortex answers
What should intelligent workers do with that knowledge?
16The product surface
Sixteen working screens, not marketing placeholders.
SenseMesh is an operational platform. These are the surfaces your data, semantic, governance and AI teams work in every day.
screen 01
Enterprise Intelligence Map
domain-level intelligence coverage, drillable to dataset
screen 02
Data Source Explorer
1 240 discovered sources, classification and connection state
screen 03
Meaning Graph
entity, policy and process relationships with provenance
screen 04
Ontology Studio
canonical concepts, taxonomies and semantic versioning
screen 05
Semantic Mapping Studio
concept ↔ source-field mappings and confidence review
screen 06
Intelligence Product Builder
compose, version and expose agent-ready products
screen 07
Agent Opportunity Explorer
ranked agent opportunities with value and gaps
screen 08
Agent Readiness Dashboard
seven-dimension readiness by domain and use case
screen 09
Data Quality Cockpit
scoring, conflicts and AI-recommended remediation
screen 10
Lineage Explorer
source-to-decision traceability for every answer
screen 11
Governance Centre
policies, sensitivity, consent, approvals and audit
screen 12
Connector Marketplace
cloud, on-premise, hybrid and legacy connectors
screen 13
Industry Pack Library
sector ontologies with tenant extensions
screen 14
AI Sensemaking Assistant
natural-language operation with visual results
screen 15
Global Administration
platform, tenancy, residency and key management
screen 16
Tenant Administration
users, roles, connectors and agent authorisations
SenseMesh
Make your organisation understandable to AI.
Start with an agent readiness assessment of one business domain. You will see your connected systems, semantic coverage, governance gaps and the agent opportunities already within reach.