AI reshaped how software gets built. This is what the AI Factory's website should be: not a brochure — a working demo of the product. Pick your industry, watch the agent work, leave with a blueprint.
Inventory that watches itself. Dead stock surfaces before it costs you.
you ›
0 weeks
kickoff → live MVP
not 6–8 months
$0K
working capital surfaced
dead stock found in audit #1
day 20
month-end close moved
from day 20 to day 1
0%
pilot NPS
finance team, reference case
Proof, not promises
Every number the agent says comes from a tool call, and every write is a draft behind your approval. Try the gate yourself.
Scripted simulation · the live version runs on a real multi-tenant ERP
X-ray · tool trace
The three-pillar claim, upgraded
The original site asserts three capabilities. The v2 site lets you verify each one on the page.
Former business owners and product managers who have felt these problems from the inside — the spec is written in business outcomes, not jargon.
they start with your P&L
World-class software engineers shipping systems with tests, CI, migrations and audit trails from day one — not prototypes held together with tape.
tests · CI · RLS · migrations
LLM experts who treat agents as production components: tool-calling, grounding, approval gates, evals and cost caps — not a chatbot bolted on.
tool-calling · evals · guardrails
the guardrails the demo above runs on
Approvals
writes are drafts until a human clicks
Grounding
numbers come from tools, never model memory
Evals
agent behavior asserted in CI on every push
Cost caps
token budget per run, tracked per tenant
Isolation
row-level security — tenants can never overlap
Audit
every action logged with actor and timestamp
Results, not adjectives
Same six engagements as the original site — rebuilt as interactive stories: filter by industry, open the approach, see the before → after.
Large manufacturer, >$10M revenue. Inventory lived in spreadsheets; dead stock was invisible until it hurt.
$250K+
Dead stock identified
in the first audit
6 weeks
Time to live
from kickoff
$40M business. Accounts were closed 20 days into the next month — every decision was made on stale numbers.
1st
Books closed
day of the month, down from day 20
−19 days
Decision lag
fresh numbers for the whole month
Month-end close, visualized
Time compressed for illustration (~2400×). Reference case: $40M business.
$20M B2B distributor. Deliberately off payment gateways; matching transfers to invoices ate the finance team's week.
Minutes
Match time
previously days of manual matching
Kept
Finance team
control — every match is confirmed
Corporate legal department. Contracts were scattered across inboxes and drives; renewals slipped through.
Zero
Renewal surprises
since go-live
Seconds
Contract lookup
with cited sources
$20M B2C client. Offers were configured manually and pushed blindly — no loop between purchase behavior and promotions.
Minutes
Offer setup
previously a developer ticket
Visible
Purchasing behavior
per segment, per campaign
B2C platform wanted to launch a personal finance tracking tool — AI-enabled — as a new value-added service.
100%
NPS (finance team)
after pilot
Shipped
Launch
as an MVP in weeks, not quarters
Metrics reference the public case studies on uang.ai · expanded narratives are concept illustrations
Do the math yourself
The original site says “high ROI”. Here you set your numbers and watch the estimate move — assumptions stated, methodology linked.
Process to automate
0 h/mo
capacity released
$0/yr
process cost saved
≈ $0
working capital potentially locked in dead inventory
The 4-step model, with receipts
Same four steps the original site promises. Here every step opens to show what you actually receive.
Artifact · Spec excerpt
§3.2 Restock rule — SKU is LOW when qty < min_stock
§3.3 Agent drafts one PO per supplier, never sends
§5.1 Approval gate — Approve/Deny UI, audit row per decision
Transparent, then interactive
Three components, no hidden costs. Pick a column and compare what you actually get.
from $22K
One-time build of the solution, scoped to your requirements. You own the outcome.
~18–20% / yr
Recurring license for the solution — updates, improvements and new agent capabilities.
optional
Optional. Hosting, monitoring, support SLA and a human who answers.
Fit to your process
✓ Built around your process
Time to value
✓ 6–8 weeks
Adapts when you change
✓ Change requests + agents absorb routine change
Routine work
✓ Agent drafts the work, human approves
3-year TCO shape
✓ Setup + flat license, predictable
You own the leverage
✓ Your spec + your AI workflow
The textarea is dead
Answer five quick questions — the concierge composes a scoped solution blueprint with timeline, guardrails, similar cases and an indicative price range. No database, no signup wall: the result lives in a shareable link.
Blueprint concierge
step 0/6
Straight answers
No. This is an independent redesign concept built as a portfolio pitch: it shows what the AI Factory's website could become. All referenced case metrics come from uang.ai's public website; expanded narratives are concept illustrations.
The demo on this page is a scripted simulation so it works instantly and costs nothing — the trace format, tool calls and approval gate mirror the real implementation. The live reference app (UangLite) runs a real LLM agent with tool-calling and human approval, and this site's blueprint concierge uses a real LLM when a key is configured, with a deterministic fallback when it isn't.
Your answers are composed into a blueprint and encoded into the shareable URL. There is no database and no tracking — the blueprint lives entirely in the link. Don't include secrets; this is a demo.
Because that's how enterprises actually adopt agents. The agent reads freely and drafts writes; a human approves each one. It creates the audit trail auditors want and the trust your team needs. Full automation can be unlocked gradually, action by action, once the trust is earned.
AI has compressed both specification and implementation. The 4-step model front-loads the painful 20% of the process, ships it working, then iterates. The reference cases on the original site (6-week inventory system, day-1 close) came from exactly this discipline.
One-time setup fee to build, an annual license for the solution (~18–20%), and optional hosting & support. The blueprint concierge gives you an indicative range based on your scope before any conversation.
Questions about this website itself — what's real, how it's built, where your data goes — are answered on the Q&A page.