ShhAI Invoices
Invoices → learning decision support that captures your way of working, recommends the next best action with clear reasons and confidence, drafts or sends under your policy, and adapts to payment outcomes - silently and intelligently , inside your Google Workspace.
Why it matters
No guesswork, no missed follow-ups, and no need to buy an accounts receivable platform, bolt on a separate artificial intelligence module, or change how you work. ShhAI Invoices turns open invoices into a ranked, explainable chase list and can action it for you ( draft-only, approve-to-send, or fully automated). It’s an artificial intelligence decision support system that connects the dots between your rules, the actions taken, and how each payer responds; it then intelligently adapts, learning from the link between actions and results, to fine-tune recommendations so you pull cash forward, increase on-time payment, and reduce touches.
What “intelligently adapts” means (practically)
Action → result learning: Tracks which combinations of tone, timing, channel and spacing led to faster payment, and prefers those patterns (within your policy).
Timing: Shifts send-times to when a payer is most responsive, inside your business-hours window.
Tone: Chooses the level (friendly vs firmer) that historically resolved faster for that payer.
Cadence: Adjusts spacing and escalation so low-yield nudges drop away and high-yield touches happen sooner.
Priority bands: Moves invoices up or down based on patterns that actually brought payment forward for similar cases.
Confidence & thresholds: Updates confidence and gentle thresholds (e.g., escalate at 10 vs 14 days) from payment timing and other connected outcomes.
It does not rewrite your policies; it adapts within your guardrails and shows its reasoning on every recommendation.
What runs in the background
Works the way you already work in Google Workspace. Use whatever you have today - a shared spreadsheet, folders of invoice documents, or email threads. A short mapping step aligns your setup to a simple, standard shape (for example, a Google Sheet or a comma-separated file), so you don’t need to reorganise anything.
Policy and guardrails first. Your tone, contact limits, business-hours window, and hardship rules create day-one consistency and set safe boundaries for all actions.
Explainable decisions. A clear, editable policy scorecard turns today’s signals (such as days past due, last contact, average pay-lag, broken promise-to-pay, amount versus client tier) into an initial recommendation with reasons you can see.
Learning that changes recommendations. A compact artificial intelligence model learns from what actually happens next — especially whether and when payment arrives (and other outcomes where connected). Each week it updates confidence, priority bands, timing and contact approach, so future recommendations and priorities adapt to your clients’ behaviour.
Configurable actioning. Choose how recommendations are executed: draft-only, approve-to-send, or fully automated across the channels you already use - all within your policy and guardrails.