Private AI — on your infrastructure

Sovereign AI Infrastructure
for the Enterprise.

Deploy fully private, enterprise-grade LLMs within your own secure cloud perimeter. Zero data leakage. Zero external API dependencies.

Start a proof of conceptSee how it works
Data never leaves your environment
RBAC and full audit logging
On-prem or private cloud
andita://security-ledger/live
LIVE
Incoming Query Log0 req
Waiting for queries...
System Metrics
Local Token Throughput
100 tok/s
-30s-20s-10snow
Vector DB Connection
HEALTHY
Prevented Data Leaks
0
All inference running on-prem.
Zero tokens transmitted externally.t+0
Business Outcomes

Results, not features.

Six measurable improvements, consistently observed across deployments.

Get an ROI estimate
3–5×

Faster decisions across teams

60–80%

First-level support load reduced

+40%

Productivity gain for knowledge workers

–30%

Operational cost in data-heavy functions

100%

Policy-governed, fully auditable

0

Data sent to external models or public cloud

Based on observed performance across comparable enterprise deployments. Results vary by organization and scope.

Private AI architecture

How Andita works.

Six layers — from raw data to governed AI output — entirely within your infrastructure.

01 / 06

Connect your data sources

Andita connects to your document stores, databases, and business systems. Data is ingested without replication to any external environment.

SharePoint, Google Drive, network drives, email archives

PDF, Word, Excel, and scanned documents via OCR

SQL databases, REST APIs, ERP and CRM connectors

Incremental sync — only changed content is reprocessed

02 / 06

Structure and index content

Raw content is cleaned, normalized, and indexed into a queryable knowledge layer. All processing runs on your infrastructure.

OCR with layout preservation for scanned and mixed-format documents

Entity extraction — names, dates, amounts, clauses

Semantic chunking and embedding generation on-premises

Encrypted at rest and in transit throughout

03 / 06

Surface relevant content

A hybrid retrieval pipeline combines semantic search and keyword precision to surface high-confidence results from your knowledge base.

Vector similarity search over embedded document corpus

BM25 keyword ranking fused with semantic scores

Cross-document retrieval for comparison and validation

Source attribution with every retrieved chunk

04 / 06

Generate grounded outputs

A private language model generates responses grounded in your retrieved content — not the open internet.

Responses cite source documents with page and section references

Structured outputs: summaries, comparisons, reports

Confidence scoring on support drafts and recommendations

Constrained to retrieved context — no hallucination from external sources

05 / 06

Govern every output

Every output passes through a governance layer before reaching users. Access is scoped by role. All interactions are logged.

RBAC — outputs scoped to the user's permissions

Output validation against schemas and business rules

Audit trail: query, sources, response, user, timestamp

Configurable content filters and confidence thresholds per use case

06 / 06

Managed operations, continuously

Andita runs the system post-deployment. You receive performance reports and strategic reviews. No internal AI function needed.

Weekly performance and usage reporting by team and use case

Continuous model fine-tuning on new content

Anomaly detection and latency monitoring

Quarterly reviews aligned to your business outcomes

Platform Architecture

Three layers. One sovereign stack.

Every layer is independently deployable, privately hosted, and fully air-gappable.

Discuss your use case

Security Layer

The Private Gateway

Intercepts, scrubs PII, and securely routes internal enterprise queries in real-time.

  • Real-time PII detection and redaction
  • Zero-trust query routing pipeline
  • Full audit trail on every interaction
Request a demo

Retrieval Layer

Sovereign RAG Engine

Securely indexes your local ERPs, internal wikis, and databases without external API tracking.

  • Private vector store — no third-party embeddings
  • Connects to ERPs, wikis, and internal databases
  • Incremental indexing with access-level filtering
Request a demo

Inference Layer

Local-Node Deployment

Ultra-optimized open-source LLM layers running directly on your private VPC or on-prem hardware.

  • Runs entirely within your private VPC or hardware
  • Quantized models tuned for enterprise workloads
  • Air-gapped deployment option available
Request a demo

All three layers are available as a Complete Sovereign Bundle — deployed on a shared private infrastructure with unified governance and monitoring.

View bundle pricing
Data Perimeter Flow

How data moves — and stays — inside your perimeter.

Unstructured data streams in from ERPs, databases, document stores, and employee queries. No filtering applied — raw signals enter the perimeter edge.

STEP 1: RAW INGESTION
raw_payload.json
1{
2 "source": "erp.internal",
3 "type": "raw_query",
4 "payload": {
5 "user": "[email protected]",
6 "query": "Show Q3 EBITDA for EMEA",
7 "card_ref": "4929-XXXX-XXXX-1234",
8 "timestamp": "2024-11-12T09:14:33Z"
9 },
10 "pii_scan": false,
11 "routed_to": "perimeter_edge"
12}

The Private Gateway intercepts every payload. PII entities, credit card patterns, internal metrics, and named entities are detected, scrubbed, and replaced with anonymised tokens before any model contact.

STEP 2: PERIMETER CLEANSING

Sanitised, token-safe payloads reach the local inference node. The model responds entirely within your VPC — no data ever leaves the perimeter boundary.

STEP 3: PRIVATE LLM EXECUTION
Why Andita

Why organizations
choose Andita.

Book a Discovery Call

Data sovereignty

Runs on your infrastructure. No external model access, no shared tenancy, no data leaving your perimeter.

Knowledge on demand

Staff get accurate answers from verified internal sources — instantly. No waiting, no searching, no asking around.

Support load reduced

Routine queries resolved before they reach your team. High-value work gets attention; repetitive work is absorbed by AI.

Configured to your model

Access rules, knowledge sources, tone, and escalation paths are yours to define. No generic defaults.

Scales without headcount

One deployment serves new teams, geographies, and use cases as you grow. Cost stays predictable.

Audit-ready from deployment

RBAC, immutable logs, and compliance-aligned architecture — ready for board, legal, or regulatory review at any point.

Industries

Where Andita
is deployed.

Organizations where data requirements are strict, oversight is expected, and AI cannot operate as a black box.

Enterprises

Unify knowledge and automate operations across complex org structures — without exposing data to public AI infrastructure.

Financial Institutions

Strict data segregation, RBAC, and audit-ready logging — aligned with the governance requirements of regulated financial environments.

Government & Education

Sovereign deployments that keep data within jurisdictional boundaries. Offline and air-gap options for classified or restricted contexts.

Healthcare & Legal

Privacy-first architecture for sectors where data handling obligations are non-negotiable. No third-party model access, ever.

Built for

Mid-sized Institutions

200–800 employees

Organizations with real operational complexity but no dedicated AI function. Andita handles deployment, management, and improvement — you direct the outcomes.

Large Organizations

800–2,000+ employees

Enterprises managing knowledge, workflows, and compliance across multiple teams or geographies. Andita provides a single governed platform for all of it.

Implementation Path

From first call
to live operations.

Four phases. Clear deliverables at each. No open-ended engagements.

01Week 1

Discovery & Scoping

A focused session to assess your data environment, identify the highest-value starting point, and define measurable success criteria.

02Weeks 2–4

Proof of Concept

A working private AI deployment against your real data. You see the outcome before any subscription commitment is made.

03Weeks 5–8

Subscription Onboarding

Managed operations begin. Andita handles infrastructure, integrations, and team enablement. You maintain full control.

04Ongoing

Continual Enhancement

Scheduled model reviews, usage analysis, and proactive improvements — delivered as part of the subscription. No internal AI team needed.

POC-first. Andita does not ask for a subscription commitment before you have seen the outcome on your own data.

Request a Discovery session
Commercial model

Commercial model.

Validate before committing. Pay for what you activate. Every engagement begins with a proof of concept.

01 — Proof of Concept

Start with a working deployment.

A time-boxed POC scoped to one use case — your real data, your infrastructure, your team. You see results before any long-term commitment.

02 — Module Subscription

Activate the modules you need.

After the POC, move to a monthly subscription for one or more modules. Infrastructure is included. Pricing is fixed — no usage billing, no token charges.

03 — Managed Support

Ongoing operation handled for you.

A predictable monthly support model covers monitoring, updates, optimization reviews, and your team's questions. No internal AI function required.

04 — Broader Deployment

Expand on your terms.

Add modules, business units, or geographies when the time is right. Advanced configuration and additional capacity are available as your needs grow.

Need advanced configuration or higher capacity?

Enterprise infrastructure, dedicated environments, and custom integration scope are available. Pricing is discussed directly — no public table.

Discuss your requirements
Security & Trust

Security and control,
by design.

Every control is structural — not a setting. Built for organizations where data handling is a hard requirement.

Private deployment

On-premises, private cloud VPC, or dedicated hosted tenancy. No shared environments, no external model access.

End-to-end encryption

Encrypted in transit and at rest using your key management. No plaintext outside your perimeter.

Granular RBAC

Access is controlled by roles you define — scoped to knowledge sources, modules, and admin functions.

Immutable audit logs

Every query, response, user, and timestamp recorded. Tamper-evident, exportable, and inspection-ready.

Air-gap capable

Fully isolated operation with no external network dependency — for classified or high-security environments.

Regulated-sector architecture

Aligned with data handling requirements in banking, healthcare, government, and legal. Documentation available on request.

Get Started

Start a conversation.

A 45-minute session — no pitch, no commitment. We assess your environment and determine whether Andita is the right fit.

Book a Discovery Call

We respond within one business day.

Andita is the right conversation if:

  • Data privacy or sovereignty is a hard constraint on your AI adoption.
  • Operational workload is growing and headcount cannot scale at the same rate.
  • Institutional knowledge is embedded in documents, systems, or senior staff rather than accessible.
  • Previous AI pilots did not reach production.
  • You need AI that is governed, auditable, and privately operated — not a SaaS tool.
4–6 wks

to first value

POC-first

validate before subscribe

Fixed

monthly pricing