Enterprise AI Solutions for Regulated Industries

AI That Works
In Production

Secure, auditable AI solutions for DACH enterprises. From document intelligence to autonomous agents — deployed on your infrastructure.

On-Premise
Deployment Available
GDPR
& EU AI Act Compliant
Security-First
Architecture & SOC 2 Roadmap

Benchmarked against academic multi-hop QA standards

56.7%
Exact Match on MuSiQue
vs ~20% Naive RAG
84%
Exact Match on 2WikiMultiHopQA
vs ~42% Naive RAG
65%
Exact Match on HotpotQA
vs ~27% Naive RAG
Rigorous Evaluation

Tested on 500+ samples per benchmark using standard academic multi-hop QA datasets — MuSiQue, HotpotQA, and 2WikiMultiHopQA.

Industry-standard benchmarks
Cost Efficient

Achieves GPT-4 level accuracy using cost-effective gpt-4o-mini — thanks to Graph-ReAct architecture that compensates model size with smarter retrieval.

10x cheaper than GPT-4 pipelines
Production Scale

19,000+ documents indexed with 260,000+ knowledge graph triplets. Entity resolution improved graph connectivity from 1% to 46%.

Real-world document volumes
Enterprise Knowledge Infrastructure

ARGUS: The Reasoning Engine for Enterprise Knowledge

Stop building chatbots that just keyword-search.
Start building AI that investigates, reasons, and answers correctly.

The "Last Mile" Problem in Enterprise AI

You've ingested thousands of PDFs, contracts, and technical manuals into your vector database. Yet, your AI assistant still fails at complex questions.

It hallucinates facts that don't exist.
It misses connections between documents.
It gives you an answer, but can't tell you why.

Standard RAG is blind to context. ARGUS changes the game.

What Makes ARGUS Different?

We moved beyond simple vector similarity. ARGUS combines a Knowledge Graph with an Autonomous Agent to simulate how a human expert solves problems.

1. Multi-Hop Reasoning

It Connects the Dots

Where standard AI gives up if the answer isn't in one paragraph, ARGUS investigates.

The Query:

"How does the liability clause in the 2024 addendum affect the original 2020 master agreement?"

The Process:

Reads 2020 agreement → Finds link to 2024 addendum → Compares clauses → Synthesizes answer

Result: Answers that require logic, not just retrieval.

2. Full Auditability & Transparency

Trace of Thought

Black box AI is a liability. ARGUS provides complete reasoning transparency.

Evidence Ledger

Every claim is cited with a direct link to the source document.

Reasoning Log

See exactly which steps the agent took and how it reached the conclusion.

Benefit: Your compliance team will actually approve it.

3. Enterprise-Grade Accuracy

Strict Source Grounding

Built on hybrid architecture (Graph + Vector + ReAct), outperforming standard retrieval on complex logical benchmarks.

100%

Answers Cite Sources

Every claim is backed by a document reference. No source? No answer.

Designed for the C-Suite & IT Security

We know that great algorithms don't matter if they don't fit your infrastructure.

Security First

On-Premise Ready

Deploy via Docker in your private cloud or VPC. Your data never leaves your perimeter unless you want it to.

Cost Efficient

Smart Routing

We achieve GPT-4 level results using cost-effective models (like GPT-4o-mini) thanks to our advanced graph filtering.

Agnostic & Flexible

Model Independent

Plug in OpenAI, Azure, Anthropic, or run local LLMs (Llama 3, Mistral). It's your choice.

Verified Performance

Proven Performance: The Numbers Don't Lie

We didn't just build a wrapper around ChatGPT. We benchmarked ARGUS against rigorous academic datasets designed to break standard search systems.

Naive RAG (single-query vector search) struggles with multi-hop questions.
ARGUS actively investigates and connects facts across documents.

HotpotQA

Multi-step Retrieval

F1 Score

38%
83.1%

Exact Match (EM)

27%
65%
Naive RAG
ARGUS

Naive RAG fails: Bridge Problem: Finds first fact, but misses the second document needed for the complete answer.

MuSiQue

Deep Logic Chains (3-4 steps)

F1 Score

20%
68.4%

Exact Match (EM)

12%
56.7%
Naive RAG
ARGUS

Naive RAG fails: Too complex: Questions require 3-4 steps. Single search can't retrieve all necessary pieces.

2WikiMultiHopQA

Complex Reasoning

F1 Score

42%
89.2%

Exact Match (EM)

32%
80%
Naive RAG
ARGUS

Naive RAG fails: Partial answers: Often answers only part of compound question or loses critical details.

Results achieved using cost-effective models (gpt-4o-mini). Performance scales further with larger models.

260K+
Semantic Triplets
Subject-Relation-Object knowledge units
19K+
Documents Indexed
Ingested and cross-referenced
46.4%
Graph Connectivity
Up from 1% via entity resolution
6–13s
Full Reasoning Latency
End-to-end, including multi-hop traversal

Why These Metrics Matter for Your Business

F1 Score = Precision + Recall

High F1 means the system finds the right information AND includes all relevant details — not just partial answers from page 5 of Contract A.

Exact Match = Production Ready

High EM means the answer is exactly right — critical for compliance, legal, and financial use cases where "close enough" isn't acceptable.

"Training-Free" Efficiency

We achieved these scores using a zero-shot approach. You get this accuracy out-of-the-box on your data, with no expensive model training required.

Ideal Use Cases

Legal & Compliance

Analyze conflicting clauses across hundreds of interlinked contracts.

Technical Support

Solve L3 tickets by connecting error logs to specific legacy manuals and resolved Jira tickets.

Financial Analysis

Synthesize quarterly reports from multiple subsidiaries into a single coherent summary.

Technical Specs (For the Engineering Team)

Architecture

Hybrid Search (RRF) + Personalized PageRank (PPR) on Knowledge Graph

Agent Framework

Custom ReAct with loop detection and memory compression

Stack

Python, PostgreSQL (pgvector), Docker-compose

Zero-Training

No fine-tuning required. Ingest data and start asking immediately.

Knowledge Graph Scale (Internal Benchmarks)

260K+
Semantic Triplets
19K+
Documents
46.4%
Connectivity
6-13s
Query Latency

Don't Settle for "Good Enough" Search

Your business data is complex. Your AI should be too.

Book a Demo

See ARGUS solve a query your current chatbot failed on.

Our Services

Full spectrum of AI solutions to transform your business

Document Intelligence for Legal

Automated contract analysis, clause extraction, and liability gap detection across 10,000+ documents with source-cited answers.

Compliance Automation

BaFin, DORA, and EU AI Act readiness — automated audit trails, risk assessments, and regulatory reporting for financial institutions.

Enterprise Knowledge Graphs

Connect SAP, Salesforce, and SharePoint into a unified AI-powered knowledge layer with multi-hop reasoning across your data.

Legacy Data Rescue (OCR + AI)

Digitize decades of maintenance manuals, engineering specs, and handwritten records — making tribal knowledge searchable and actionable.

On-Premise LLM Deployment

Llama 3, Mistral, and Qwen on your infrastructure. Full data sovereignty with Docker-based deployment — your data never leaves your servers.

AI Readiness & Team Training

Discovery workshops, GenAI readiness audits, and hands-on training for technical teams — from prompt engineering to RAG architecture.

Why Choose Heabsy

We don't just implement technology — we become your strategic partner on the path to AI transformation. Every solution is tailored to your unique business needs.

Tailored approach to every project
24/7 support at all stages
Flexible engagement models

Contract Review: 6 Weeks → 3 Days

A legal team audited 10,000+ contracts using ARGUS — reducing review cycles from 6 weeks to 3 days with full clause-level traceability.

Legal & Compliance

Audit-Ready in 72 Hours

Financial institutions automated BaFin/DORA compliance checks — cutting audit preparation from weeks to days with full evidence trails.

Finance & Banking

30 Years of Know-How, Searchable

A manufacturer digitized 1,500+ legacy maintenance manuals via OCR and knowledge graphs — preserving decades of tribal expertise before key retirements.

Manufacturing

Zero Data Leaves Your Perimeter

On-premise deployment with Llama 3 & Mistral models. Your documents stay on your servers — no cloud, no third-party access, full data sovereignty.

Security & Compliance

Ready to Start AI Transformation?

Book a free consultation. We'll analyze your business processes and recommend the right AI solutions.

Headquarters
Vienna, Austria

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