RAVEN.Nest
Financial document AI
that never leaves the building.
Sovereign, on-premise processing for Europe's fiduciaries.
1001 AI LABS · BASEL, SWITZERLAND · PRE-SEED 2026
The Problem
Manual entry costs more than a fiduciary can bill
THE COMPLIANCE TRAP
US CLOUD Act exposure: cloud AI routes client tax and payroll data through US-owned infrastructure.
Swiss nLPD: processing personal financial records in multi-tenant clouds raises data-protection and documented-handling obligations.
members (CH)
fiduciary practices
A paper-heavy back office in every practice.
Full TAM / SAM / SOM on the Market slide.
Illustrative model · ~300 docs/mo at CHF 35/h loaded cost · target base ~250,000 paper-heavy SMEs. Bottom-up estimates.
02 / 16Why Now
New rules are pushing financial data off the cloud
Documented handling and data-residency duties, in force with no grace period since 2023.
France now requires every VAT-registered business to receive structured e-invoices; Factur-X (PDF/A-3 + XML) is the default format. Swiss fiduciaries with French or multinational clients must read and archive the XML, not just the PDF.
GoBD demands immutable, documented audit trails. EU AI Act high-risk rules for financial AI apply from Dec 2027, with documentation duties already active.
Regulatory scope varies by jurisdiction; phased rollouts; counsel review required.
03 / 16The Solution
Sovereignty by design
An on-premise AI appliance. The documents never leave the client's building.
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01
Data never leaves the building
Capture, OCR, extraction and review all run on the client's own node. Document contents stay on-site, so there is no US CLOUD Act vector.
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02
Local AI, zero cloud calls
On-device inference on Ollama and llama.cpp with Apertus 8B to 70B. No external API, no data egress, no per-document cloud cost.
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03
Human in the loop
Every extraction is reviewed on a local dashboard before it is used. Nothing is booked automatically.
Architectural isolation on client-controlled hardware. Hardware configuration under validation.
04 / 16The Real ROI
From cost sink to advisory engine
Automation hands each fiduciary back the hours they can bill as advisory.
Today
25 h/mo manual entry · −CHF 725/mo loss · 70% of hours trapped
With RAVEN
10 to 30 sec/doc · billed CHF 0.10 / 0.50 / 3.00 per doc by pipeline depth · 22.5 h/mo freed
Reallocate to advisory
At CHF 150/hour → yields +CHF 3,375/mo new billing
Value transfer
At 20 SMEs, unlocks
advisory potential per fiduciary firm
Illustrative model (300 docs/SME/mo · CHF 35/h loaded · CHF 150/h advisory · 20 SMEs/firm). To validate in pilot; not realised revenue.
05 / 16Market
Fiduciaries are the wedge into a wider regulated market
BASEL → UPPER RHINE → DACH → FRANCE → EMEA → UAE (PEPPOL / PINT-AE)
B2B2B · THE CHANNEL
Bottom-up scenario. Official counts sourced (BStBK, TREUHAND|SUISSE, KSW); the 20 to 50 multiplier is an operating assumption to validate in pilots. ARR modelled on the entry tier, not committed revenue.
06 / 16How It Works · 1 of 2
The whole pipeline runs on one node in the office
Scan / Ingest
Capture documents from any source.
Local OCR + Extraction
Extract text and data entirely on-premise.
Human Review
Validate accuracy and resolve exceptions.
Structured Archive / ERP-ready
Store securely and integrate with your systems.
Current tested mode keeps processing local on client-controlled hardware; ERP integration is a roadmap item.
07 / 16How It Works · 2 of 2
Nine layers turn paper into reviewable books
LAYERS
LAYERS
LAYERS
Runtime: Ollama / llama.cpp · Apertus 8B to 70B (GGUF) · zero external API calls · human-in-the-loop before any booking.
08 / 16The Killer Use Case
We clear the quarterly shoebox at its source
In DACH fiduciary practice, “the shoebox” is the bag of mixed paper (receipts, invoices, bank printouts, handwritten notes) a client drops at their Treuhänder each quarter.
Disorganized, multi-format, multi-language, often incomplete. Today the accountant sorts, transcribes and reconciles each document by hand, one at a time.
THE COST · PER TREUHAND FIRM, MONTHLY
- Ingests every format at once, no manual sorting
- Local pipeline extracts VAT, amount, counterparty, date, category
- Human-reviewed output in 10 to 30 sec per document
- Pushes structured data to Bexio / Abacus / DeepBox
- Audit trail stored locally, nLPD compliant, no cloud
- Scan a receipt on the phone
- On-device pipeline: OCR, vision, validation, Swiss audit
- Outputs Factur-X / QR-Bill / ZUGFeRD for the accountant
- Sends straight to the Treuhänder's RAVEN node
Cost ranges are illustrative fiduciary-practice estimates. the on-premise RAVEN node is the MVP today; Corvue is an early-stage idea, built once a pilot proves the need.
09 / 16Validation · Beta Sandbox
A local agent fetches and reads real receipts
Raven MCP Scout, a local MCP agent, logs into the supplier and downloads receipts itself with Playwright, then RAVEN processes them. Local LLM only, zero cloud. Beta-tested on Coop.
WHAT WE SCANNED
INDUSTRIES
Gastronomy · retail · trades & industry · health & pharma distribution
FILE TYPES
Handwritten receipts · multi-page invoices · bank statements · expense notes
WHAT WORKS TODAY
- Reads mixed document formats
- Extracts amounts and entities
- Identifies Swiss VAT
- Runs fully offline, on-device
- Human review before export
SELECTED & REGISTERED
Pre-revenue, pre-seed. Figures come from three offline sandbox runs (provenance in appendix). Still to validate: accuracy on live client data · reconciliation at scale · ERP connectors · recurring willingness to pay.
10 / 16Business Model
Own the node, then pay per finished document
Agent-as-a-Service. One setup fee covers the on-premise node, which the client owns; after that they pay only for finished, booked-ready output.
CapEx-neutral on day one. Nothing leased.
The floor tier: capture only.
Priced by document complexity and pipeline depth.
Setup recovers the hardware; the per-document fee is software margin, because local inference costs almost nothing to run.
Pilot pricing under validation; no locked rates pre-revenue. Flat monthly plans and a full-local-ledger concept are in the appendix.
11 / 16Competition & Defensibility
On-premise plus fiduciary depth: an empty quadrant
▲ On-premise, client-owned hardware · Fiduciary-specialized ▶
Nutanix · Dell AI PCs · local LLM kits
Local, but general-purpose. No fiduciary pipeline or appliance.
On-site appliance + DACH fiduciary pipeline: a combination incumbents don't currently offer.
Findea.ch · Klippa · Mindee · WellyBox
Client data transits US-owned infra: CLOUD Act exposure.
Bexio AI · Abacus
Strong ledgers, cloud-first, no on-site AI extraction layer.
Team & Ecosystem
A founder built for this exact problem
Ten years inside regulated back-offices. The exact stack RAVEN needs, in one founder:
Solo-built RAVEN end to end · 513K+ LOC · Python · FastAPI · PostgreSQL · fully local
COUNSEL & ECOSYSTEM
Roadmap hire: part-time Senior Systems Engineer for node hardening. Anchors are counsel/incubator/mentors, not backers. Einzelfirma; AG planned.
13 / 16The Ask
Four ways to help build the nest
Swiss CLA · CHF 2M cap · 20% discount · 2% p.a. · 24 months
18-month runway. First 3 fiduciary pilots · AG incorporation · senior engineer.
Use of funds: 35% engineering & deployment · 25% pilot hardware · 20% AG + IP filings · 20% Basel customer development.
Fiduciary or accounting firm. Run RAVEN on your documents for 60 days, no commitment, full sovereignty. Named as a founding design partner.
→ alaasalathe@1001ailabs.com
Receive a RAVEN Scout node on-site. 60-day pilot with your real document corpus; we handle setup, support and reporting.
→ 3 slots · Basel region priority
A finance or AI researcher (PhD, postdoc, or university student) to co-develop and benchmark local document AI on Swiss data. Innosuisse / academic fellowship route.
→ university collaboration welcome
18-MONTH MILESTONE MAP (targets)
First design partner signed · benchmark locked
2 to 3 pilots live · first nodes deployed on-site
5 to 10 fiduciary clients · nodes across the Basel region
Seed round · DACH expansion (Freiburg, Mulhouse)
20+ nodes deployed · founding team in place
Targets, not guarantees. Swiss AG planned; pre-revenue. Indicative terms subject to due diligence. alaasalathe@1001ailabs.com
14 / 16Join the Journey
What we're building, and who we need to build it
WHAT WE'RE BUILDING NOW
Hardening the on-premise node and its agentic pipeline. We are coding the next build at the HPE & NVIDIA Agentic AI Hackathon, on NVIDIA hardware.
A local MCP agent that logs into a supplier and downloads receipts itself with Playwright, then hands them to RAVEN. Local LLM only. Beta-tested on Coop.
Mobile scan app for SMBs. An early-stage idea, built once a fiduciary pilot proves the need.
THE FIRST TEAM · FOUNDING HIRES
Three ground-floor roles, meaningful equity, shaping the company from day one.
Corvue is an early-stage idea, not a shipped product.
15 / 16Appendix
Every claim traces back to a document
Three-trial register: A 632/476 · B 427/1,534 · C 128/391 → 1,187 / 2,401, Level-A/B grading.
DSO2026013123 (V1.0) + DSO2026013134 (V1.1), ZertES-signed.
513,271 LOC / 892 files, root SHA-256, sole-ownership declaration.
Local MCP agent auto-downloads supplier receipts with Playwright (beta on Coop); RAVEN processes them. Protocol + PDF/A-3 outputs.
Setup fees + hardware BOM (Scout 32GB to Enterprise 192GB, preliminary). Alternatives to the pay-per-output lead model: flat monthly plans (capped at a document allowance) and the full-local-ledger concept.
Local-only isolation architecture.
Data room being assembled now. INPI e-Soleau + ZertES establish date-certain proof of authorship and anteriority.
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