Enterprise AI platform

A secure, model-agnostic AI execution platform for regulated enterprises

Built end to end, from architecture to production: governed workflows, secure retrieval and agents, audit trails and cost visibility designed in from day one.

Torno gave us delivery continuity with better cost control than any of our previous partners. AndrewInvestor Partner, DAIS
Industry
Enterprise AI for regulated industries
Client stage
Investor-backed, growth stage
Engagement
18 months, ongoing
Delivered by
Hybrid Sprint Pod, onshore and offshore
Services
AI Product Engineering
The challenge

Most AI pilots never become production systems, because governance, access control and cost control get bolted on too late.

  • Ingest high volumes of enterprise data securely
  • Multi-tenant from the start, ready for a go-to-market rollout
  • Tight compliance and launch deadlines
  • Governance built in, not retrofitted after launch
What we built

What the Pod delivered.

01

Secure ingestion

Source documents and enterprise systems connected, with policies applied and metadata classified before data reaches any AI workflow.

02

Retrieval and agents

Chunking, embeddings and vector storage that keep lineage and access context, plus agent design with tool boundaries, hallucination controls and fallbacks.

03

Model-agnostic query layer

Retrieves only authorized context, routes to the chosen LLM and records every step. No model lock-in.

04

Governance and observability

Identity and role-based access, audit logs, query history, and workflow-level cost visibility.

05

Cloud and DevOps

Infrastructure as code, CI/CD, monitoring, secrets and release controls.

Workflows shipped on the platform

One platform, many governed workflows.

Hedge funds

Real-time sector and event intelligence for portfolio managers.

Accounting firms

Document intake, missing-item tracking and audit-ready visibility for tax-return preparation.

How it went

The path, step by step.

  1. FoundationIngestion, embeddings, LLM integrations, RBAC, logging
  2. SecurityEncryption, data residency, compliance reporting, auditing
  3. OptimizationQuery history, analytics, team dashboards
  4. ExtensibilityAPIs, SDKs, webhooks, governance dashboards
Weeksto a production-grade first build, with less rework
Multi-tenantarchitecture ready for the go-to-market rollout
No lock-inroute each task to the best model
MeasurableAI cost, by workflow
Built with
RAGAgentsVector databasesLLM routingRBAC / ABACInfrastructure as codeCI/CD
Start here

Want results like these?

Tell us what you need built, modernized or made smarter.

Book a 30-minute call → Topic: An AI layer
  1. 1
    A 30-minute callWe learn what you need and where it hurts.
  2. 2
    A clear planScope, team and the first two sprints.
  3. 3
    Work in daysA Pod starts, and ships every two weeks.