The Vision · Interactive preview

Describe an agent.
Watch it build itself.

Loom is a visual agent canvas embedded in MindloomHQ. Drag-and-drop, AI-assembled from plain English, with governance, evals, and a one-click production deploy — all auto-wired. The canvas is the Python. Graduate from no-code to engineer without re-learning a thing.

See the wow ↓Skip to future ideas

The 90-second arc

A non-developer ships a production agent. In ninety seconds.

Type a description → three AIs negotiate → governance wires itself → evals generate → deploy → live URL. End to end.

Step 1 · Personalize

What's your industry?

Finance ✓HealthcareSaaSRetailEducationGovernment

Step 2 · Describe

✨“Compliance review for new account openings — KYC checks, AML flags, escalate suspicious cases.”Assemble ↻

Step 3 · Three AIs negotiate

[Planner] Starting with a webhook trigger for account-open events. Adding identity-verification, AML lookup, and a decision node.

[tool_call] emit_node({type:"trigger", subtype:"webhook"})

[tool_call] emit_node({type:"llm", subtype:"classify_identity"})

[Auditor] Account-opening payloads contain PII (name, SSN, DOB). Inserting redaction before the LLM. Audit log on every decision. HIL threshold 0.85 for AML escalation.

[tool_call] emit_governance({node:"n2", pii_redact:true, audit:true, hil_threshold:0.85})

[Tester] Generating 5 evals — happy approval, AML-flagged case, expired ID, PII safety, performance under burst.

[tool_call] emit_eval({name:"AML-flagged account triggers human review", ...})

Step 4 · Canvas assembles (with governance auto-wired)

📥Webhook→🛡️Injection guard→🔒PII redact→🤖Identity check→🔍AML lookup→✋HIL ≥0.85→✅Approve / 🚩 Flag

Yellow nodes were auto-inserted by the Auditor. Builders can configure but not disable when org policy locks them.

Step 5 · Evals run

Valid account opening — clean approval✓ 1.2s · $0.003

AML-flagged source → escalates to human✓ 1.4s · $0.004

Expired ID → returns 400 with reason✓ 0.3s · $0.000

PII (SSN, DOB) never leaves redaction boundary✓ 1.1s · $0.003

100 sequential calls — p99 latency✓ p99 2.1s · $0.31

5/5 passing · $0.32 total · 5.7s

Step 6 · Deploy

$ loom deploy account-opening-compliance
  Compiling canvas → LangGraph Python ✓
  Provisioning Vercel Fluid Compute ✓
  Wiring webhook ✓
  https://mindloomhq.com/loom/you/account-opening-compliance
  Live · monitoring on · 0 reqs · $0.0031 / req est.

That's the whole arc. Industry chip → describe → three AIs negotiate → canvas assembles with governance baked in → evals pass → deploy. Production agent, end to end, no code.

Layer 01

Multi-agent visible assembly.

Not one AI building your workflow — three named AIs visibly collaborating. Planner drafts the graph. Auditor demands governance. Tester writes evals. Their conversation streams in real time while the canvas assembles. AI thinks out loud.

Why this matters

Most AI tools hide the model behind a wall. Loom makes the reasoning visible — and divides it across roles a non-technical viewer instantly understands: the one who plans, the one who keeps it safe, the one who tests it.

No other no-code tool does this. Bubble doesn't think out loud. n8n doesn't reason. Voiceflow doesn't audit. This is what “agentic” actually looks like.

[Planner] Refund triage needs a webhook entry, then a classifier for the request type.

[tool_call] emit_node({type:"trigger"})

[tool_call] emit_node({type:"llm", subtype:"classify"})

[Auditor] PII risk — refund text contains customer emails. Inserting redaction before the LLM.

[tool_call] emit_governance({node:"n2", pii_redact:true})

[Tester] Generating evals for the happy path, edge cases at the threshold, and the PII boundary.

[tool_call] emit_eval({name:"$24 refund auto-approves"})

Layer 02

Auto-eval generator.

The difference between a toy and a production agent. Loom watches what you're building and generates a full test suite across five classes — happy path, edge / boundary, error path, governance, performance. Click run → all pass / fail with diff. This is the missing piece every CTO has been waiting for.

Happy path

$24 refund · valid receipt

Auto-approves.

✓ 1.2s · $0.003

Edge

$50.01 · over threshold

Must escalate, not approve.

✓ 1.4s · $0.004

Error

Malformed payload

Returns 400, doesn't crash.

✓ 0.2s · $0.000

Governance

PII never leaks

SSN + email redacted everywhere.

✓ 1.1s · $0.003

Performance

p99 < 3s

100 sequential calls.

✓ p99 2.1s · $0.31

Total

5 / 5 passing

$0.32 · 5.7s · audit-clean.

Layer 03

One-click deploy. Real URL. Live observability.

Most no-code tools end at “save.” Loom ends at “shipped.” Click Deploy → real URL on mindloomhq.com/loom. Hit it from Postman immediately. Live dashboard shows cost, latency, and a per-request trace. Rollback in one click.

Refund triage agent · v3

https://mindloomhq.com/loom/you/refund-triage

● Live

Requests · 24h

1,847

Cost / req

$0.0031

p50 / p99

1.2s / 2.4s

Decisions

62 · 27 · 11%

Recent requests · click for per-node trace

14:23:08 · approved order 3091 · $24.50 · 1.1s · $0.0028

14:23:01 · flagged order 3090 · $87.40 · 1.4s · $0.0034 · amount over threshold

14:22:54 · approved order 3089 · $12.99 · 0.9s · $0.0024

14:22:47 · escalated order 3088 · $39.00 · 2.1s · $0.0042 · confidence 0.78 below HIL 0.85

Layer 04

Governance, baked in. Not bolted on.

For regulated industries — finance, healthcare, government — this isn't a feature. It's a requirement. Every Loom agent ships with PII redaction, immutable audit logs, human-in-loop thresholds, prompt-injection guards, and SOC2-grade exportable logs.

What gets auto-wired

🔒 PII redact · before every LLM call
📜 Audit log · per reasoning / decision node
✋ Human-in-loop · below confidence threshold
🛡️ Injection guard · at every trigger
📊 SOC2-ready logs · exportable, retention-locked

Per-org policy (admin-locked)

# loomrc.yaml — what your CISO writes once
governance:
  pii_redact: required  # builders cannot disable
  audit_log: required
  hil_min_confidence: 0.85
  injection_guard: required
  retention: 7 years  # SOX-aligned

Layer 05

Personalized for the viewer.

One click before the demo. The workflow becomes your industry. Finance sees KYC compliance. Healthcare sees patient intake triage. SaaS sees lead routing. Retail sees returns. Not a generic demo — a 'this was built for me' experience.

What's your industry?

Finance ✓HealthcareSaaSRetailEducationGovernment

Demo updated: KYC compliance review for new account openings

Generated demo workflow

📥Account open event→🔍KYC verify→🔍AML check→🤖Risk score→✅Approve / Escalate

Layer 06

Composable agents. Lego for AI.

Drag a deployed agent as a node into a new one. Build complex multi-agent systems by composing simpler ones. Each sub-agent runs with its own audit log and cost trace, rolled up under the parent.

Customer Support Orchestrator (parent agent)

📥Webhook→🤖Intent classify→📦Sub: Refund triage+📦Sub: KYC verify→✅Respond

Sub-agents are real, deployed agents elsewhere. Their inputs become this node's inputs, outputs become its outputs. Full audit + cost trace rolls up to the parent run.

Layer 07

Multiplayer canvas. Figma for agents.

Real-time co-edit. Live cursors. Inline comments pinned to nodes. Branch a canvas, propose changes, get reviewers to approve via PR-style review — with merge gates on governance policy.

Refund triage · branch feat/add-pii-stronger

ABC3 live

📥Webhook→🔒PII redactB→🤖Classify→✅Output

Reviewer B · 12:08

“Should we also redact full names here?”

1 review requested · 0 approvals · governance check pending. Merge blocked until org policy passes.

Layer 08

Self-documenting share page.

Every deployed agent auto-generates a polished page: README, architecture diagram, curl example, compliance badges, fork button. Every agent built becomes a forwardable marketing asset.

mindloomhq.com/loom/you/refund-triage

Refund triage agent

An agent that classifies incoming refund requests, looks up the order, and either auto-approves under $50 or routes to a human reviewer. PII-redacted, audit-logged, SOX-retention.

✓ 5/5 evals passing🔒 PII-safe📜 Audit-logged🏛️ SOX 7yr retention$0.0031 / req · 1.2s p50

Architecture

📥Webhook→🔒PII→🤖Classify→🔍Lookup→✅Decide

How to use it

$ curl -X POST mindloomhq.com/api/loom/you/refund-triage/invoke \
  -d '{"order":"3091","amount":24.50}'

Want one like it?

Fork into your account. Modify. Deploy under your own URL.

Fork ↗

The progression

From no-code to engineer. Same canvas the whole way.

Most platforms teach you no-code or code. MindloomHQ takes you all the way through with a cert at each step. Track 02 unlocks Code mode. Track 03 unlocks engineering-grade nodes. The surface never changes — only what you can do with it.

Track 01

No-Code AI Builder

12 lessons. Typebot · Bubble · Make · n8n. Build chatbots, doc extractors, and lead-qual bots.

🏅 Cert: 'No-Code AI Builder'.

Track 02

AI Automation Engineer

15 lessons. n8n deep-dive, Zapier AI, Make. Multi-step automations with HTTP, conditionals, memory. Code mode unlocked.

🏅 Cert: 'AI Automation Engineer'.

Track 03

Agentic AI Engineer

10 phases · 96 lessons. Graduate to Python. Ship a multi-agent system with evals, governance, deployed URL.

🏅 Cert: 'Agentic AI Engineer'.

Future enhancements · V2+ candidates

What comes after the eight layers.

Documented for transparency, not committed. Each is a candidate to pick up after V1 launches and real usage data exists. Effort key: S small (one phase) · M medium (multiple sprints) · L large (quarter-scale) · XL extra-large (often non-engineering).

#	Candidate	Why it would matter	Effort
F1	Production traffic replay	Replay last N requests against new agent version before promoting. Risk-averse industries love this.	M
F2	AI cost-optimization meta-agent	Watches your deployed agent and suggests 'swap Sonnet → Haiku here, save 70%.'	S
F3	Voice-first build	Describe agents out loud. Mobile-friendly. Accessibility win.	S
F4	Agent benchmarks	Public leaderboard comparing your agent's accuracy / cost / latency against community agents.	M
F5	Cross-org agent marketplace	Sell agents you've built. Revenue split with platform. Network effects.	L
F6	Federated learning across agents	Anonymized telemetry improves AI-Assembly suggestions for similar tasks platform-wide.	L
F7	Custom node SDK	Orgs build their own node types pointing at internal APIs. Enterprise tier.	M
F8	Auto-regression-tests from prod failures	When prod has a bad decision reported, Claude auto-writes an eval that catches it next time.	S
F9	Agent versioning + diff view	Every save = snapshot. Visual diff between versions (graph + Python side-by-side).	S
F10	Live debugging on prod traffic	Pause an agent mid-execution on real traffic, inspect state at each node. DevTools for agents.	M
F11	Native ChatGPT / Claude.ai install	Embed Loom inside other AI products. Distribution leverage.	S
F12	Mobile app for canvas	iOS / Android for monitoring + simple edits. Push notifications on eval failures.	L
F13	Org-level dashboards	All agents in your org, total cost, total decisions, compliance posture.	S
F14	Code review by Claude on graph changes	Every save → Claude reviews the diff with inline comments. PR-style on solo edits.	S
F15	Agent contract testing	Formal pre/post-condition specs enforced at runtime. Engineering-grade safety.	M
F16	Auto-translated curriculum	Lessons + canvas hints translated into 8+ languages. International expansion.	S
F17	Real-time multi-agent collab (agents talk)	Multiple agents on one task negotiating in real time, conversation visible. The 'AGI demo' angle.	L
F18	Compliance certs (formal)	Pursue actual SOC2 Type II, HIPAA BAA, GDPR audit. Becomes 'certified,' not 'ready.'	XL

Want to follow this build?

Start with the No-Code AI course — twelve lessons, free, you ship a working AI app by lesson 12. The visual canvas builds out across the next several phases.

Start the No-Code AI course →Back to /no-code

$ loom deploy account-opening-compliance Compiling canvas → LangGraph Python ✓ Provisioning Vercel Fluid Compute ✓ Wiring webhook ✓ https://mindloomhq.com/loom/you/account-opening-compliance Live · monitoring on · 0 reqs · $0.0031 / req est.

Auto-eval generator.

# loomrc.yaml — what your CISO writes once governance: pii_redact: required # builders cannot disable audit_log: required hil_min_confidence: 0.85 injection_guard: required retention: 7 years # SOX-aligned

Candidate

Why it would matter

Effort

Production traffic replay

Replay last N requests against new agent version before promoting. Risk-averse industries love this.

AI cost-optimization meta-agent

Watches your deployed agent and suggests 'swap Sonnet → Haiku here, save 70%.'

Voice-first build

Describe agents out loud. Mobile-friendly. Accessibility win.

Agent benchmarks

Public leaderboard comparing your agent's accuracy / cost / latency against community agents.

Cross-org agent marketplace

Sell agents you've built. Revenue split with platform. Network effects.

Federated learning across agents

Anonymized telemetry improves AI-Assembly suggestions for similar tasks platform-wide.

Custom node SDK

Orgs build their own node types pointing at internal APIs. Enterprise tier.

Auto-regression-tests from prod failures

When prod has a bad decision reported, Claude auto-writes an eval that catches it next time.

Agent versioning + diff view

Every save = snapshot. Visual diff between versions (graph + Python side-by-side).

F10

Live debugging on prod traffic

Pause an agent mid-execution on real traffic, inspect state at each node. DevTools for agents.

F11

Native ChatGPT / Claude.ai install

Embed Loom inside other AI products. Distribution leverage.

F12

Mobile app for canvas

iOS / Android for monitoring + simple edits. Push notifications on eval failures.

F13

Org-level dashboards

All agents in your org, total cost, total decisions, compliance posture.

F14

Code review by Claude on graph changes

Every save → Claude reviews the diff with inline comments. PR-style on solo edits.

F15

Agent contract testing

Formal pre/post-condition specs enforced at runtime. Engineering-grade safety.

F16

Auto-translated curriculum

Lessons + canvas hints translated into 8+ languages. International expansion.

F17

Real-time multi-agent collab (agents talk)

Multiple agents on one task negotiating in real time, conversation visible. The 'AGI demo' angle.

F18

Compliance certs (formal)

Pursue actual SOC2 Type II, HIPAA BAA, GDPR audit. Becomes 'certified,' not 'ready.'

Describe an agent.Watch it build itself.

A non-developer ships a production agent. In ninety seconds.

Multi-agent visible assembly.

Why this matters

Auto-eval generator.

One-click deploy. Real URL. Live observability.

Governance, baked in. Not bolted on.

What gets auto-wired

Per-org policy (admin-locked)

Personalized for the viewer.

Composable agents. Lego for AI.

Multiplayer canvas. Figma for agents.

Self-documenting share page.

Refund triage agent

From no-code to engineer. Same canvas the whole way.

No-Code AI Builder

AI Automation Engineer

Agentic AI Engineer

What comes after the eight layers.

Want to follow this build?

Describe an agent.Watch it build itself.

A non-developer ships a production agent. In ninety seconds.

Multi-agent visible assembly.

Why this matters

Auto-eval generator.

One-click deploy. Real URL. Live observability.

Governance, baked in. Not bolted on.

What gets auto-wired

Per-org policy (admin-locked)

Personalized for the viewer.

Composable agents. Lego for AI.

Multiplayer canvas. Figma for agents.

Self-documenting share page.

Refund triage agent

From no-code to engineer. Same canvas the whole way.

No-Code AI Builder

AI Automation Engineer

Agentic AI Engineer

What comes after the eight layers.

Want to follow this build?

Describe an agent.
Watch it build itself.

Describe an agent.
Watch it build itself.