Docs-grounded answers.
Sage answers from product documentation and a code-derived domain-knowledge layer, not from a generic web crawl. Every answer is anchored to how the product actually works, not what an internet article speculates.
An assistant that understands the product. Not your data.
New hires take weeks to learn how the product models the firm. Composite questions (T&M plus three ARR licenses, subcontracted on vendor paper, co-sell with partner-sold and vendor-sold) are not in any single help article because the answer lives in how the product itself is built. Sage is a Claude-powered help assistant grounded in PartnerView's product documentation and a code-derived domain-knowledge layer. It answers how-do-I-model questions, walks decision guides like retainer vs MSP vs T&M, and runs troubleshooting trees for margin, rev-rec-to-QBO, and commission. Sage is privacy-safe by design: no access to your live business data, no access to source code, and graceful declines on business-judgment and data-prediction questions. It points you to the right screen instead. Independently leak-tested to confirm no internal details escape in answers.
There is no scalable, docs-aware help that understands the product's modeling vocabulary. Senior staff burn hours answering the same configuration questions, and new hires wait for a free shoulder to lean on.
How do I model T&M plus three ARR licenses? Subcontracted on vendor paper with a co-sell? The answer is the product's own logic, stitched across modules. No help center article covers the combination.
A general-purpose chatbot does not know PartnerView's vocabulary, invents fields that do not exist, and may exfiltrate context it should never see. Privacy posture has to be the differentiator, not a footnote.
Retainer vs MSP vs T&M, billable vs non-billable utilization, deal-stage gating rules. The trade-offs the data model actually surfaces are scattered across senior staff and the occasional Loom. Nothing centrally walkable.
| A generic AI chatbot | PartnerView | |
|---|---|---|
| Grounding | Web-grounded; answers from a generic crawl. | Docs-grounded; answers from PartnerView documentation and a code-derived domain-knowledge layer. |
| Domain awareness | Generic; does not know your product's modeling vocabulary. | Knows the product's own vocabulary for T&M, ARR, retainer, MSP, co-sell, subcontract, rev-rec, commission. |
| Business-judgment questions | Makes a prediction or invents a recommendation. | Declines gracefully. Points you to the right screen and the human who owns the call. |
| Business data access | Unknown. Often pastes prompts into a third-party context window. | No access to live business data. No access to source code. No internal identifiers in answers. |
| Leak testing | Unknown. Trust the vendor. | Independently leak-tested. |
Sage answers from product documentation and a code-derived domain-knowledge layer, not from a generic web crawl. Every answer is anchored to how the product actually works, not what an internet article speculates.
T&M plus multiple ARR licenses, subcontracted-on-vendor-paper, co-sell with partner-sold-and-vendor-sold. Sage knows the product's own modeling vocabulary and walks the configuration end to end.
Walk through retainer vs MSP vs T&M, with the trade-offs PartnerView's data model actually surfaces. Sage explains what changes in commission, rev-rec, utilization, and reporting under each choice, then points you to the right screen to configure it.
Margin not matching, rev-rec to QBO not posting, commission calculating wrong. Sage walks the diagnostic step by step, naming the screen and field to check at each branch.
Sage does not act on your behalf. It explains the answer and points you to the screen that holds the data. The decision and the click stay with the human operator.
Sage has no access to your live business data and no access to source code. It declines business-judgment and data-prediction questions gracefully. No internal identifiers appear in answers. Independently leak-tested.
Sage retrieves from the indexed help corpus (help articles, the User Manual, the Feature Catalog) at query time using SQLite FTS5 keyword retrieval and synthesizes only from the retrieved excerpts. It is not a model-as-database pattern. When retrieval is weak, Sage returns a 'not covered' response with a link to the help index and makes no API call. The corpus is re-indexed at every deploy, so the assistant's knowledge equals the shipped help content.
Docs-grounded answers to the composite questions that no single help article covers.
Walkable decision guides and step-by-step diagnostic trees grounded in the product's own logic.
The trust boundary that makes Sage safe to ship with the rest of the product.
Org-wide controls that let an admin shape and bound how Sage operates inside the firm.
A docs-grounded assistant that knows the product. Not your data. Not your code. Independently leak-tested.
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