I've seen a dozen vendors pitch "AI document analysis" for compliance. Most of them are glorified PDF highlighters. We have a real problem: our team has to review 50+ page vendor security and privacy policies against our internal checklist before onboarding. It's a manual, soul-crushing time sink.
So I threw Kimi at it. Not for a demo, but to run it against actual documents from last quarter. Here's the raw setup and results.
**The Workflow:**
* Created a master checklist in a plain text file (e.g., `SOC2_Type2_required, Data_encryption_at_rest_required, Data_portability_required`).
* Fed Kimi the checklist and a new vendor policy PDF via the API.
* Asked for a simple JSON output: `{ "checklist_item": "met | not_met | not_found", "extracted_text_supporting_decision": "quote" }`
**What Worked:**
* **Accuracy on explicit claims:** If the policy said "We encrypt all data at rest using AES-256," Kimi nailed it. `Data_encryption_at_rest_required: met`.
* **Speed:** It processed a 60-page PDF in about 45 seconds. Beats a human's 90 minutes.
* **Handled poor formatting:** Scanned PDFs with wonky OCR? It managed better than I expected.
**Where It Got Stuck (The Real World Part):**
* **Implied compliance:** A policy saying "We use industry-standard cloud infrastructure" doesn't explicitly mention SOC2. Kimi often flagged this as `not_found`, where a human would infer it. You need *very* literal checklist items.
* **Ambiguity is a killer:** "Data is protected in accordance with best practices" returned `not_met`, which is correct but too broad. It can't ask follow-up questions.
* **API cost:** Running this against our backlog of 200+ policies would add up. You need to justify the time saved versus the spend.
**Bottom Line:**
Kimi is a powerful filter, not a final reviewer. It's excellent for triage—flagging the 80% of policies that are clearly compliant or clearly deficient. The 20% in the grey zone still need a human eye. We're now using it to cut the first-pass review time by about 70%.
If you're doing similar work, your checklist design is everything. Be painfully specific. Don't ask for "GDPR compliance." Break it down into "Right to erasure process defined," "Data Processing Agreement offered," etc.
- No fluff.
The speed gain is undeniable, but I'm skeptical about the blind trust in a "met" or "not found" designation for compliance. This approach assumes the checklist is the whole universe of risk.
What happens when the document says "Data is encrypted" but doesn't specify the standard or the key management? That's a "met" on a naive checklist, but a glaring hole in a real security review. The tool parses what's written, not what's omitted or deliberately vague, which is where most vendor policies get slippery.
Have you run the same document through a second model to compare outputs? I did that last month with a similar setup and got conflicting "met" statuses on three key items, all because of ambiguous phrasing. The time saved on the first pass just got added back in manual verification.