We deliver auditable, high-accuracy AI at highest scalability for all enterprise documents by replacing slow, high-cost LLM/RAG solutions with SLM-bootstrapped Claim-Graphs.
2026 | amini@deepentix.com
A real-world example: Our pharma pilot partner needs to research competitor drugs for their new development.
Total corpus → filtered to 15,000 highly complex documents requiring expert extraction.
The maximum throughput of expert researchers working manually with no path to scale.
Standard LLM pipelines are slow, expensive, and must repeat from scratch for every new metric.
Sample documents are submitted for semantic profiling.
Results are verified and refined through iteration with expert input.
Graph pipeline is specialized using synthetic training data for accuracy.
The full corpus of trials turns into a specialized claim graph.
Queries are submitted via API to the graph, providing full provenance for every answer.
Saving 12-15X in processing time and 7-9X in cost compared to SOTA LLMs.
This solution can be deployed across a 1.1 million document corpus, effectively mitigating the inadequacies of traditional keyword filtering and providing deep, auditable insights.
We ground consuming LLMs with connected facts and multi-hop reasoning chains — eliminating hallucinations at the source, not after the fact.
Specialized Small Language Models are 10x cheaper than generic 70B parameter models. They excel at granular extraction tasks and dramatically reduce error rates in domain-specific contexts.
Every answer traverses a fully verifiable chain: Answer → Claim → Paragraph → Document → Author. Built for regulators, not retrofitted for them.
Unlike hyperscalers, our lightweight SLM architecture deploys on-premise or in private regional clouds. Zero data leakage of clinical or financial IP, non-negotiable in regulated industries.
EU AI Act + Solvency II make explainability mandatory. Claim‑level provenance turns compliance from manual to built‑in.
CER rework and claims appeals are costly. Verifiable answers shorten reviews, reduce rework, and unlock STP.
95% of AI enterprise pilots have not led to any ROI (MIT, 2025). Graph x GenAI is mainstream. Big gap in specialized solutions remain open.
AI Middleware & Knowledge Graphs (2025)
EU Pharma/MedTech & BFSI (2025)
DACH Pharma/MedTech + Insurers
Legend: ✅ native • ◑ partial/via partner/custom • ✕ not core
We provide the platform that empowers YOUR team to build graphs.
Stop renting intelligence; start building assets.
CEO
- 3x tech startup founder
- Users from 150+ countries with 5-star reviews
- PhD Numerical BioMech, TU Wien (250+ citations)
CTO
- Ex-Salesforce ML Architect
- 15 years Silicon Valley enterprise AI experience
- AI Fellow, EuroCC Austria
CKO
- Sr. Mgr. Deloitte, Leading Knowledge-enriched AI
- Sr. Res. Fellow Knowledge Rep., VU Amsterdam
- PhD Knowledge Eng. (50+ publications), U Leipzig
CFO
- CFA charterholder
- $10M+ raised across 3 companies
- 34% MoM growth track record
- Pilot 1 (Pharma, Switzerland): Auditable protocol workflow automation.
- Pilot 2 (Pharma, Germany): New drug competitor analysis pipeline.
- MVP (Biomed., SciPub+): Knowledge gap-based hypothesis generator.
- 5 new pilots planned for 2026
- €270k aws DeepTech Grant.
- €2.5M grant pipeline
- TIB partnership: collaboration on the expert SLM project with Prof. Auer's team at the TIB with iver 2 decades of experience in Neurosymbolic Graphs
Business Model
€Fixed per indexing/query API call
We host and operate the workflow and graphs;
Free graph indexing with a 12‑month contract. Simple pricing; we will adjust as we learn.
€160k/year license
Customer runs their own graph;
Customer bears infrastructure/cloud costs
Up to 1,000 documents / 20k claims ingested and 1,000 API calls included.
Private SLMs, custom ontologies, fine‑tuned deep research tools, audit exports.
- Related solution vendors
- Consultancies/boutiques (e.g., Deloitte partner units)
- CTO's 15+ yrs experience with SV Enterprise AI solutions
- CKO’s 10+ yrs as Senior Knowledge Solutions Manager @ Deloitte → partner pathways.
- Pilot success
Project start
INiTS incubation
Core team onboarding
Team of 4
MVP + PoC in Pharma
€270K AWS Pre-Seed Deepetech Grant
Team of 7
Goal: Technology Validation with 5 pilots
Raising 1M (€300K + €700K)
Team of 12
Goal: Product-Market Fit
Series A prep (Incl. FFG & AWS Seed)
