SFTWTRS.AI
ENTERPRISE AI · WTRDB
WTRDB
2026 THEME · KNOWLEDGE GRAPHSKnowledge graphs you will enjoy building.
WtrDB is our visual platform for building and managing knowledge graphs. Teams model assets, people, processes and data as connected entities and watch the picture take shape. It is also the graph engine inside Wtr.Scene, Wtrospai, Wtr.Aegis and our compliance platform.
IN PLACE OF A VECTOR DATABASE
WtrDB replaces the vector database in your organisation with a more structured approach to agentic reasoning: agents follow typed relationships, rules and sources. A natural fit for Digital Transformation teams, compared on Explore.
What it does
Visual graph builder
Draw entities and links, with no queries to write
50 to 70% less time to model a domain
Bring data in from anywhere
Spreadsheets, databases, APIs and documents
40 to 60% less data mapping effort
Consistency you can trust
Sheaf-theoretic checks catch contradictions
60 to 80% of source conflicts caught before use
Ready-made templates
Ten templates, each for three to five uses
50 to 70% faster start than a blank schema
Grounding for AI
Facts that LLMs and agents can cite
20 to 35% more accurate answers
Open to your graph platform
Built on a fast open graph engine, and designed to sit alongside Neo4j and Azure Cosmos DB estates
How you can deploy it
Managed cloud
We host and run it
Your cloud tenant
Azure or other clouds
On premises
Data stays on site
Pricing
Per gigabyte used
EXPECTED IMPACTTypical ranges from comparable deployments; results vary by site
30 to 50%
fewer made-up answers
40 to 60%
less time to find answers
30 to 40%
faster staff onboarding
25 to 40%
lower process run cost
IN PRODUCTION At a power EPC company, alongside Wtrospai for logistics and warehouse data
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
SFTWTRS.AI
ENTERPRISE AI · WTRDB · HOW IT WORKS
HOW IT WORKS
2026 THEME · KNOWLEDGE GRAPHSStructure your agents can reason over.
Most AI programmes start with a vector database that retrieves text that looks similar. WtrDB replaces it with a governed knowledge graph, so agents reason over typed relationships and rules.
THE STRUCTURED ALTERNATIVE
Two ways to give agents a memory
THREE-FILTER GOVERNANCE
Every fact earns its place
Sheaf checks catch contradictions between sources, and every accepted fact keeps its lineage.
HOW AGENTS CONNECT
Brain Endpoints
One governed graph serves apps, agents over MCP and live streams, with access checked on every call.
BUILT FOR DIGITAL TRANSFORMATION TEAMS
Expected impact · typical ranges, results vary by siteIn place of a vector store
Typed relationships, rules and sources for agents to reason over
20 to 35% more accurate answers
Fits the stack you have
Files, ERP and APIs connected once; agents connect over MCP
40 to 60% less mapping effort
Governed from day one
Policy checks, lineage and access rules built in
60 to 80% of conflicts caught early
Nilesh AI Systems Pvt Ltd · sftwtrs.aiExplore
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Tell us what you want to see, understand or protect better.
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