For finance teams · Excel · Slack · Teams · your own data stack
AI drafting layer for month-end close, GL reconciliation, variance bridges, and audit-ready evidence. Drafts run inside the Excel and Slack you already use — your financial data never leaves your stack.
=YIG("summarise this table") IC matching, GL recon, variance bridges, schedule prep — drafted from the data already in your stack. No re-platforming.
Every output flows through your team’s review. Comments, edits, accepts, rejections — all logged with reviewer and timestamp.
Approved outputs land in your close folder, board deck, or audit binder. Yig disappears. Your workflow stays yours.
Community and SMB flagship. The drafting engine — 40+ tools, multi-step planning, native IM integration. Runs in Slack, Teams, Feishu, Excel, and any terminal. Every output passes your reviewer before it ships.
Learn more →Governance, SSO, audit trail, and multi-tenant management for institutions. Built for security teams and compliance-first organizations.
Learn more →Finance and data integration layer. Consensus across sources, structured extraction, and automated reconciliation. Sold separately.
Learn more →
Yig inside Excel, PowerPoint, and Word. Bring your own API key —
no backend required. Use =YIG() formulas
in any spreadsheet.
5 minutes. Q2 close. Watch the agent ship a board pack.
Watch full demo (4:34) →Select the one that best describes your situation — we'll recommend the right product.
We'll notify you when the product is ready. No spam — only updates worth reading.
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Roadmap vote · Yig Finance
Which data source does your team use?
Vote to determine which connector we build first.
Live results show the stack distribution of users on the waitlist.
"Every month-end, we manually reconcile SAP data against three Snowflake tables. That alone takes three days — before close can even start."
"We have four different Excel files tracking the same KPI. Every time the CFO asks which one is right, nobody in the room can give a straight answer."
"My analysts spend 60% of their time cleaning and formatting data. Less than 40% on actual analysis. That is not what I hired them for."
Indicative time targets
Manual baseline vs. review-only with Yig. Targets, not achieved customer outcomes — see footnote.
| Task | Manual baseline | With Yig (review-only) |
|---|---|---|
| Intercompany reconciliation¹ | ~1.5 days | ~2 hours review |
| GL reconciliation² | ~6 hours / month | ~45 min review |
| Variance bridge for board deck³ | ~4 hours | ~30 min review |
| Audit schedule prep⁴ | ~2 days | ~3 hours review |
Run Yig locally or in your own cloud. No mandatory SaaS data plane. No vendor-side data lake.
Reviewer, timestamp, input, output, and diff written to an append-only audit log. SOX-friendly.
Claude, GPT-class, or self-hosted. You own the inference contract. Switch models without losing workflows.
Data flow, audit-log model, reviewer gate, and security boundaries — all published as public spec articles. Inspectable before purchase.
Closed beta · Python 3.11+
Once you have access
$ yig --version
yig 1.6.0
$ yig thinker init
●
● ●
→ thinker · 32 tools loaded
model claude-opus-4-7
ctx 200k tokens
$ yig workflow gl_recon --period Q2-2026
∴ running gl_recon template…Distributed via private beta · not on PyPI
Delivery surfaces
Runs where you work
# CLI / TUI
$ yig thinker run "Q2 close analysis"
# IM bots (Feishu / Teams / Google Chat)
@yig-thinker run gl_recon for Q2
# Excel / PowerPoint / Word
Yig Office Add-ins · Excel beta · BYOK
# REST API gateway
POST /v1/run · FastAPI · WebSocket