Loom Studio

For enterprises · early access

12–18 months of AI infrastructure. Compressed to days.

Loom Studio is a low-code platform for production-grade AI products in regulated industries, a compliance-ready backend with REST API, audit logs, and resilience, built in from day one.

EARLY ACCESS
enterprise pilot

$ what we're building

// underwriting, claims, KYC, prior-auth, contract review

> visual builder, not a framework

✓ export as a self-contained Python project. No lock-in.

Request early access

Enterprise pilots opening in regulated verticals · no public trial yet

01. Diagnosis

The gap isn't the model

Building an enterprise AI product means mastering an unreasonably wide stack, all at once.

What you'd have to build What it actually takes
LLM orchestration Multi-agent topologiesFallback routing
Document ingestion Extraction pipelinesStructured output
Compliance PII/PHI redactionAudit trailsHIPAA/SOC 2
Deployment VersioningRollbackREST API provisioning
70% Enterprise AI initiatives that never reach production (Gartner)
40% Enterprises adding AI agents by 2026 (Gartner)
171% Average ROI on enterprise agentic AI deployments
$139B agentic AI market by 2034, 40.5% CAGR

Market figures: Gartner, industry agentic-AI market sizing. The gap is not model capability: it's the platform layer beneath it. Loom is that layer.

02. Architecture

Built like infrastructure, not a prototype

Every Loom product inherits the same production-grade foundation. Click a layer to see what it handles.

01

Documents, databases, REST APIs, SharePoint. New sources plug in without touching the rest of the pipeline.

02

Pick from a production-tested tool library, or connect external tools over MCP. No custom glue code.

03

Automatic fallback routing, retry logic, and token budget limits keep pipelines running when a single model call doesn't.

04

Every result is validated against your schema before it reaches your application. No parsing raw model text.

05

Multi-agent pipelines run concurrently and recover from missing tools or failed steps without human intervention.

06

Branching, parallel steps, multi-agent coordination: configured visually, not hand-coded per use case.

07

Real-time token streaming to your app, plus pause-and-resume approval workflows for human review.

03. How it's built

Seven steps, one guided studio

No AI engineering expertise required. The builder handles orchestration, prompt authoring, and schema design.

01
Product Definition Name, type, metadata: extraction, decision, RAG, triage, or custom
02
Schema Designer Visual data contract, auto-generated as Pydantic models
03
Pipeline Builder Drag-and-drop ingestion, extraction, tool calls, branching
04
Agent Configuration Single or multi-agent topology, tool selection, context sizing
05
Prompt Studio Structured authoring, template library, Monaco override
06
Rules Designer Decision logic as structured JSON, identical in runtime and exports
07
UI Composer Operator interface, branding, HITL toggle, export formats
04. What you get

A backend, not a workflow

Every deployed product ships with a production API, ready to call from day one.

Auto-provisioned REST API

No API design work

  • Standard REST endpoint generated for every product
  • Submit jobs and fetch results, no API design work
  • Synchronous or async polling, your choice
API · Auto-provisioned
POST /v1/jobs202
GET /v1/jobs/{id}200
GET /v1/jobs/{id}/result200
1endpoint set per product, generated automatically
Run Monitor

Visibility out of the box

  • Live and historical job status
  • Retry controls built in
  • Failure-rate visibility out of the box
Run Monitor · Live
claims-extraction-04821running
kyc-check-04820succeeded
prior-auth-04819retrying
contract-review-04818succeeded
Livestatus + retry controls, no separate tool
Human-in-the-loop review

Never a silent decision

  • Accept, edit, or reject AI outputs
  • Built-in review queue
  • Full audit trail on every decision
Review Queue · 2 pending
claim-88213pending
claim-88219pending
claim-88204approved
claim-88190edited
100%decisions logged to the audit trail
Webhook callbacks

No polling loops

  • Push approvals to your systems
  • Push job completions the moment they happen
  • No polling required
Webhooks · Delivered
job.completed → your-app.com/hooksdelivered
approval.requested → your-app.com/hooksdelivered
job.failed → your-app.com/hooksdelivered
0polling loops required
05. Verticals

Built for regulated industries

Where a wrong answer isn't a bad UX: it's a compliance incident.

Insurance Underwriting, claims assessment, property risk scoring
Healthcare Eligibility assessment, record extraction, prior auth
Financial services Credit decisions, compliance assessment, KYC automation
Legal Contract review, clause extraction, risk identification
Logistics Routing optimization, risk assessment, cargo docs
Extraction Decision RAG Custom

Four product types, one builder. Pick the shape that matches your use case.

06. Rigor

Tested before it ships

The studio is the test environment: pipelines run for real before anything deploys.

Trace Viewer See every prompt, tool call, and validation result behind a run. Nothing is a black box.
Eval Suite Batch-test against labeled samples. Accuracy, latency, and cost, measured before go-live.
Test Harness Run the full pipeline against sample inputs without deploying. Same output production would give.
07. Compliance

Compliance you don't have to build

Every product ships with the controls regulated buyers ask for on day one, not roadmap.

PII/PHI redaction

Sensitive data is redacted before it ever reaches an LLM provider.

Immutable audit log

Append-only hash-chain, 6-year retention, SIEM export. HIPAA and SOC 2 aware.

EU AI Act classification

Automated risk tier assignment: prohibited, high-risk, limited-risk, minimal-risk.

PII/PHI Redaction Built-in
EU AI Act Risk Tiers Built-in
Immutable Audit Log Built-in
JWT + RBAC Access Control Built-in
SOC 2 Type II In progress
HIPAA In progress
Ask about compliance
08. Positioning

Not a workflow tool. Not a framework.

Loom occupies the gap between the two.

↑ Production-ready output ← Less AI engineering required More AI engineering required →
Workflow automation Connects existing apps. No LLM orchestration, no schema validation.
Code frameworks Deep AI engineering expertise required. Produces code, not a product.
Loom Studio Configure, test, deploy a production backend. No framework expertise, no lock-in.
09. No lock-in

Leave whenever you want. Take the code with you.

Loom is not a workflow builder you're chained to.

Loom-hosted runtime Docker export Full Python project export

Export the entire product as a self-contained FastAPI + Docker project. No proprietary runtime dependency.

10. Get started

Two ways in

No public trial yet; pilots are hands-on by design.

Self-serve early access Get studio access and evaluate Loom against your own use case. Request access
Co-build pilot Work directly with our team to scope and ship your first product. Talk to us