Turn Fragmented Enterprise Data into Unified Intelligence
StringQL combines query language + graph database + vector search + AI to investigate across enterprise systems, public data, and documents. Built for compliance, audit, fraud detection, and AI agents.
- •Query across enterprise systems (SAP flagship), public data, and documents
- •Graph + timeline + vector search in one reasoning stack
- •Built for compliance, audit, fraud detection, and AI agents
Join 500+ SAP customers on the waitlist
How StringQL Works
StringQL is a complete reasoning infrastructure stack:
┌─────────────────────────────────────────────────────┐ │ StringBoard (Command Center) │ │ • Causal Graph • 4D Timeline • Interactive UI │ ├─────────────────────────────────────────────────────┤ │ StringRL (Audit Engine) │ │ • Deterministic reasoning (not probabilistic) │ │ • Single verifiable result with audit trail │ │ • RCA keywords: INVESTIGATE, TRACE, VERIFY, INFER │ ├─────────────────────────────────────────────────────┤ │ StringDB (Temporal-Graph) │ PageIndex (Librarian) │ │ • Stores causal flow │ • Grounds AI logic │ │ • Timeline + Graph queries │ • Evidence provider │ ├─────────────────────────────────────────────────────┤ │ Data Sources (On-prem & Cloud) │ │ SAP S/4HANA · Emails · Logs · Docs · data-zoo.de │ └─────────────────────────────────────────────────────┘
Reasoning You Can Audit. Logic You Can Trust.
Unlike GenAI (probabilistic guesses), StringRL provides deterministic proofs backed by evidence.
Built for AI Reasoning
Structured Results
Graph paths (not unstructured JSON) prevent LLM hallucination on relationships
Explainability
Every match includes the reasoning (WHY, not just WHAT)
Autonomous Monitoring
"Watch for pattern X, alert when confidence > 80%"
Example: AI Agent Investigation Flow
- 1. Agent receives tip: "Vendor 12345 might be suspicious"
- 2. Agent queries StringQL:
MATCH (v:Vendor {id: 12345})-[*1..3]-(e) RETURN e - 3. StringDB returns: Connected entities + relationships + fraud risk scores
- 4. Agent reasons: "3 shell companies, same address, circular payments detected"
- 5. Agent escalates: "High confidence fraud pattern, recommend investigation"
Why graph queries enable better reasoning: Relationships are explicit → No hallucination | Results are structured → Easy to chain reasoning steps | Patterns are reusable → Build institutional knowledge
Reasoning as a Service (RaaS)
The API for Trust
We are not another Generative AI API. We are the first "Audit Engine as a Service," designed for developers building high-trust enterprise systems that cannot afford hallucinations.
Ingestion API
POST /v1/indexFeeds the engine with unstructured data (Emails, Logs, Docs) to build the verifiable evidence foundation.
- ✓Automatically indexes all data sources
- ✓Normalizes formats (PDF, DOCX, TXT, CSV, JSON)
- ✓Creates searchable evidence library
Reasoning API
POST /v1/reasonTakes a StringRL query and returns a deterministic JSON Audit Trail, complete with a Causal Graph and deep links to original evidence.
- ✓Single verifiable result (not probabilistic)
- ✓Complete audit trail with evidence links
- ✓No hallucinations via PageIndex grounding
From Probabilistic Guesses to Deterministic Proofs.
Request API AccessThe Source of Truth for AI Reasoning
Reasoning You Can Audit. Logic You Can Trust.
SAP S/4HANA Integration
One-click connector to import master data, transactions, and audit trails as an investigative graph.
Learn more →Public Data Enrichment
Enrich with data-zoo.de: company registries, sanctions lists, beneficial ownership, financial health.
Learn more →StringQL Cross-System Queries
Unified query language across SAP + public data + your investigation notes. Find fraud patterns in seconds.
Learn more →Cypher You Know. Superpowers You Don't.
StringQL = Cypher + Timeline + Causality for investigation reasoning
MATCH (po:PurchaseOrder)
-[:TO]-> (vendor:Supplier)
WHERE po.amount > 50000
RETURN po, vendor
ORDER BY po.amount DESCINVESTIGATE root_cause
FROM PurchaseOrder('PO-45892')
WHERE status = 'DELAYED'
TRACE causality
BETWEEN Vendor AND Approval
TIMELINE [last_30_days]
VERIFY logic_path
WITH PageIndex.Source
RETURN audit_trail,
evidence,
confidenceSame Cypher you know, investigation superpowers you don't.
StringQL adds Timeline (temporal reasoning) and Causality (explain WHY) to every query. Queryable. Auditable. Trustworthy.
Learn StringQL Syntax →StringRL: Investigation-Native Keywords
RCA-specific commands that automatically trace root causes, build audit trails, and verify AI logic against raw evidence.
INVESTIGATE root_cause FROM
INVESTIGATE root_cause FROM PurchaseOrder('PO-123')Automatically traces all causal paths and builds comprehensive audit trail showing timeline, evidence sources, and confidence scores.
TRACE causality BETWEEN
TRACE causality BETWEEN Email('E-456') AND Delay('D-789')Establishes evidence-based causal relationship between two entities using temporal precedence and logical dependency.
VERIFY logic_path WITH
VERIFY logic_path WITH PageIndex.SourceValidates AI-generated logic against raw data from PageIndex. Ensures no hallucinations—every claim backed by source.
INFER missing_link WHERE
INFER missing_link WHERE context = 'logistics'Infers logical steps based on verified timestamps and workflow knowledge. Clearly marks inferred (vs observed) data.
For SAP Developers: Automate RCA for incidents (Delays, Disputes, Errors) with 80% time reduction
Explore All FeaturesBuilt for Enterprise Investigation Teams
SAP audit, compliance, procurement fraud, and supply chain risk management
Procurement Fraud Detection
"Who approved these 50 purchase orders to the same vendor?"
Visualize approval chains and vendor relationships from SAP MM/FI data. Enrich vendors with data-zoo.de to detect shell companies and conflicts of interest.
SAP Audit Trail Analysis
"Show me all changes to vendor master data in the last 6 months"
Import SAP change documents (CDHDR/CDPOS) and visualize entity evolution. Track who changed what, when, and whether it was properly approved.
Vendor Due Diligence
"Are any of our suppliers on sanctions lists?"
Bulk-enrich your supplier base with data-zoo.de. Screen against OFAC, EU sanctions, check beneficial ownership, and assess financial health.
Revenue Leakage Investigation
"Which customers have credits but no corresponding invoices?"
Graph-based queries across SAP SD/FI reveal financial anomalies that table-based queries miss. StringQL makes complex cross-module queries simple.
Join the Waitlist
Be first to access SAP connector + data-zoo.de enrichment.
Early access members get 50% off first year.
No credit card required · Launch Q2 2026