Deeplinq deploys on your infrastructure, connects your legacy systems, and leaves your data, your models, and your audit trail inside your control.
In private preview with selected financial institutions across EMEA.
A single boundary around the regulated organization. Data, orchestration, models, and governance live inside it. Sources feed in from the left; external providers connect inward from the right through scoped residency channels. Nothing crosses the boundary without being logged, evaluated, and policy-checked.
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A single, customer-controlled boundary. Data, models, orchestration, and governance live inside.
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Scoped, region-locked egress to external providers. Prompts and completions are not retained.
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Orchestration enforces policy, retrieval, and inference across every model and source.
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Every request produces an immutable, exportable record for compliance and audit requirements.
Why this exists
Regulated institutions cannot ship data to a vendor's cloud. FINMA and CCAF enforce Swiss residency. CSSF, Bank Al-Maghrib, and PDPL frame customer-data processing. HIPAA and GDPR health provisions define clinical-system egress. GxP traces pharma decisions. Solvency II, MAR, and MiFID II dictate what an auditor reconstructs.
Not edge cases. The operating envelope.
Most AI platforms were built for a different customer — one accepting hyperscaler tenancy and data paths the regulator never signed off on. Deeplinq was built for the customer who cannot.
Your orchestration, connectors, agents, model routing, and audit trail sit inside the perimeter you already defend. The platform fits the envelope — not the reverse.
Who we serve
Each surface has its own regulator, its own audit cadence, its own use cases. One platform adapts to all.
Client files and KYC reviews generate more documentation than any team can read — and secret bancaire leaves no room for external processing.
Platform infrastructure where your team builds client-file and KYC-review agents. They run inside the bank's perimeter and leave a compliance-traceable record.
KYC, credit ops, customer engagement, and transaction monitoring are measured against central banks, BAM, PDPL, MAR, and MiFID II scope.
Platform layer across onboarding, credit files, customer correspondence, and market surveillance — where your team deploys AI with national hosting and audit-grade traceability.
Patient data cannot leave the clinical perimeter, yet teams spend hours reconciling records, prior authorizations, and care pathways.
Unify clinical documents, administrative records, and protocol knowledge inside the hospital's infrastructure — HIPAA and GDPR health provisions respected by design.
GxP compliance, clinical data handling, and regulatory submissions demand audit traceability generic AI platforms cannot produce after the fact.
Bring orchestration into pharma research, quality, and regulatory affairs workflows — model-version pinning, prompt archival, decision traces for GxP scrutiny.
Classified information cannot touch commercial cloud, and most AI tooling is built on assumptions that collapse when air-gap is mentioned.
Deploy fully air-gapped on-premise — inference local, no external runtime dependency, residency enforced at the hardware boundary.
National sovereignty, procurement-compliance frameworks, and citizen-data protection make hyperscaler-backed AI non-starters at the procurement gate.
A sovereign AI layer fitting national data-protection regimes, with local hosting and the audit surface oversight bodies expect.
Solvency II, fiduciary duty, and dense policy documentation squeeze operations between regulatory scrutiny and operational load.
Infrastructure for document-intelligence, policy-review, and claim-processing agents your team builds inside the regulated perimeter — full traceability for actuarial and compliance.
What deeplinq does
The capability stack doesn't change for regulated institutions. The deployment envelope does.
Read documents, transactions, and system records at source. Extraction, embedding, and indexing stay inside the institution's environment. No training on customer data by default.
Reach into core banking systems, ERPs, CRMs, and operational databases through connectors that run where the data lives. No external data plane.
Route each query to the right model, knowledge source, and system of record. Every routing decision, retrieval, and model call is logged and auditable.
Deploy agents that propose, not decide, where the institution wants a human gate. Every action carries prompt, retrieval context, model version, and outcome — exportable for audit.
Enforce access controls at document, record, and field level. Retention, redaction, and residency through the platform — decisions versioned and reviewable.
One layered system, one perimeter. Connectors ingest, RAG engine indexes, LLM router orchestrates, agents execute — all governed end-to-end inside your perimeter.
How it deploys
Deeplinq runs entirely inside the institution's data centre. Models, vector stores, orchestration, and logs live on infrastructure the CISO already controls.
Fit signal: private banking, defense, healthcare with strict residency, public-sector.
Deeplinq deploys inside a sovereign cloud region or private-tenant environment chosen by the institution. Residency and data paths defined by the institution's contract, not deeplinq.
Fit signal: commercial banking under central-bank obligations, insurance, wealth management, sovereign-cloud healthcare.
No external network path. Inference, retrieval, and orchestration entirely on local infrastructure. Model updates and audit exports via controlled physical transfer.
Fit signal: defense, classified public-sector workloads, high-security research.
Sensitive data and regulated workloads stay on-premise or on national cloud; non-sensitive workloads extend where the institution chooses. Sovereignty boundary enforced at the platform layer.
Fit signal: universal banks with mixed workloads, multinational healthcare, pharma combining internal and external research.
12 weeks, 4 phases, co-constructed. From customer-side preparation to in-production operations, every phase is mapped — including the prerequisites on your side.
Why model choice matters
A regulated institution that depends on a single model provider inherits that provider's roadmap, data posture, and regulatory exposure. "The vendor's model produced it" is not an answer a regulator accepts.
Deeplinq treats model choice as a compliance decision. Institutions run proprietary frontier models, open-weights on local inference, or both — selected by task, sensitivity, and regulator expectation. Model versions are pinned so an auditor reconstructs a decision months later. Models replace without rewriting the platform.
Where a hyperscaler assistant or CRM-native copilot forces tenancy and a single provider, deeplinq keeps the model behind an interface the institution controls.
Currently supported
Cloud APIs (with data residency)
Open-weights (self-hosted)
Customer organization defines what's sensitive. deeplinq routes every workload to the right provider — Cloud APIs with residency controls for non-sensitive workloads, open-weights inside your perimeter for everything else.
9 providers across Cloud APIs and open-weights. Choose what fits your sovereignty posture.
How we map to your frameworks
What deeplinq does for each framework today. Coverage-in-progress is marked explicitly. Nothing aspirational.
The evidence layer
A regulator review is not won on claims. It is won on evidence. Deeplinq treats the evidence layer as first-class.
Every prompt, retrieval, model call, and agent action is archived with full decision trace — inputs, retrieved context, model version, parameters, reasoning path where exposed, human approval status where a gate applies.
Access audited at user, role, and document level. Policy changes versioned. Model-version pins prevent silent substitution.
When a regulator asks for an evidence bundle, the institution exports a structured archive. No reconstruction project. No vendor intermediary.
For banking prospects
The platform is horizontal, but banking density justifies a dedicated view — KYC, credit ops, market surveillance, customer engagement; integration footprint across Temenos, Finastra, Avaloq, Murex, SAP, Oracle.
If you are arriving from a banking mandate, the dedicated page goes deeper.
A working session with our team on your regulatory envelope, your deployment constraints, and the use cases that matter to your institution. Pragmatic, technical, short.