What is Parallel Loop?

Parallel Loop is an AI-first operating system for enterprises. It brings decisions, workflows, and organisational knowledge into one system — the foundation that makes AI work for the whole organisation.

How long does it take to deploy Parallel Loop?

5 days to your first running AI workflow. We connect to your existing systems with no migration required. A working AI agent is deployed on your infrastructure within the first sprint.

Does my data leave my environment?

No. Parallel Loop supports on-prem deployment with zero data migration. Your data stays in your environment. Zero data retention at API key level, and no provider trains on your data.

What is the Context Engine?

The Context Engine is a git-versioned repository of your organisation's knowledge — processes, decisions, workflows, and terminology. It compounds with every engagement and stays when people leave.

What LLM providers does Parallel Loop support?

Parallel Loop's LLM Gateway supports multiple providers including Vertex AI, Anthropic Bedrock, Anthropic Direct, and Azure OpenAI. It features auto-failover across providers and is flip-switchable with zero single-vendor lock-in.

What industries does Parallel Loop serve?

Parallel Loop serves enterprise teams across insurance, fintech, D2C, healthcare, logistics, energy, government, and manufacturing. The platform is industry-agnostic and adapts to any organisation's workflows.

The Context Platform

building your AI future,
without reinventing your past

Decisions, workflows, and knowledge in one system. The foundation that makes AI work for the whole organisation.

Start a Sprint Read the Memo

The Problem

Every organisation bought AI.
None built the infrastructure to operate it.

Context is scattered

Decisions vanish in meetings. Knowledge lives in heads. Data sits in silos. No single place where the organisation's intelligence compounds.

AI tools forget

Current AI is session-bound. It helps one person and resets. There's no shared workspace where human and AI knowledge builds over time.

Pilots don't scale

The industry AI failure rate is 95%. Pilots are too clean to matter. Real production means real systems, real data, real governance.

The Platform

What we build. Together.

Context Engine

Your organisation's knowledge, versioned and alive

Processes, decisions, workflows, terminology — structured, git-versioned, and made accessible to AI. Knowledge that compounds with every engagement and stays when people leave.

claims_workflow.yaml v3.2 — 2h ago

underwriting_rules.md v7.1 — 1d ago

org_ontology.json v12.0 — 3d ago

approval_matrix.yaml v5.4 — 5d ago

Ingest context

Pull from CRM, ERP, policy systems

AUTO

Reason + propose

AI analyses, flags conflicts, drafts output

Human review

Approve, modify, or reject with full audit

HUMAN

Execute + log

Deterministic execution, immutable audit trail

AUTO

Agent Harness

AI that reasons once, executes always

A customisable framework balancing inferential and deterministic workflows. AI proposes, humans approve, the system executes. Every change traceable. Every decision audited.

How It Works

From engagement to production in days

01 5 Days

The Sprint

You identify one high-friction workflow. We connect to existing systems — no migration. A working AI agent deployed on your infrastructure.

No migration On-prem Working AI

02 Weeks 2–8

First Deployment

Deploy the Context Engine. Connect CRM, ERP, legacy databases. Configure human review gates. First AI-managed workflow in production.

Context Engine Review gates Production

03 Ongoing

Platform & Scale

Expand workflows across teams. Each new workflow compounds on the Context Engine. Intelligence improves with every engagement.

Compounds Multi-team Outcome-based

Proof Point

Major Japanese insurer. Four markets. Five days.

days from engagement to running AI workflow

markets on one platform, no migration

data moved outside the client's environment

C-suite commissioned. Guidewire connected. Zero data migration.
Zero rip-and-replace. Production under a week.

Security & Compliance

Built for the most cautious CIO

Data Residency

Your data never leaves

On-prem deployment available. Cloud geo-locked per specification.

Zero Data Retention

ZDR at API key level

No provider trains on customer data — contractual and technical.

Audit Trail

Every action logged

Every prompt, response, and context change git-tracked. Immutable.

Tenant Isolation

Hard isolation by design

Separate repos, MCP connections, and containers per organisation.

Model Risk

Zero single-vendor lock-in

Multi-model gateway. Vertex AI, Bedrock, Azure OpenAI. Flip-switchable.

Explainability

Complete forensic trace

What was injected, proposed, and decided — and why. Full transparency.

A Third Way

Not a consultancy. Not a SaaS vendor.
An operating partner.

The status quo

Deployment

Traditional IT 18–36 month migrations

AI SaaS SaaS, no customisation

Org Knowledge

Traditional IT Walks out with consultants

AI SaaS Session-based, no memory

Cost

Traditional IT $10–20M/year overhead

AI SaaS Per-seat, no outcome link

Parallel Loop

Deployment 5-day sprint SOR stays on-prem. Zero migration.

Org Knowledge Compounds forever Git-versioned context repo grows with every engagement.

Cost Outcome-based Fraction of legacy. Tied to business results.

building your AI future,without reinventing your past

Every organisation bought AI.None built the infrastructure to operate it.