Models chosen per task
We match each task to the right Claude model — a fast, economical model for high-volume analysis, a balanced model for everyday work, and the most capable model for complex reasoning — and move to newer models as they ship.
We don’t add AI because every landing page has to mention it. We add AI where it actually helps ministry admins — coaching managers on review feedback, catching payroll errors before they ship, and summarizing long review datasets.
AI analyzes each manager’s review feedback — specificity, actionability, score justification — and generates coaching recommendations with priority. Editable by HR, PDF-exportable, emailable.
Learn more →AI analyzes individual review comments or batches of comments. Feedback quality score, scoring accuracy against comments, manager profile labels (Mentor / Effective / Developing / Emerging / Needs Coaching).
Learn more →AI flags pay runs that diverge from historical patterns for this employee or this period. Catches data-entry errors before the pay run is submitted.
Learn more →AI assembles a composite health and retention score per employee and writes the strengths, concerns, and issues behind it — surfacing who needs attention before it’s obvious.
Learn more →Churches that connect a ChMS can optionally include giving engagement as one signal in the health and retention scores — visible, tunable, and entirely controlled by your admins.
Learn more →We match each task to the right Claude model — a fast, economical model for high-volume analysis, a balanced model for everyday work, and the most capable model for complex reasoning — and move to newer models as they ship.
Organization-wide analysis uses the Anthropic Batch API — 50% lower cost than real-time. Results applied asynchronously without blocking UI.
Every AI-generated coaching recommendation and comment analysis is reviewable and editable by HR before it reaches a manager or goes into a report.
The prompt templates that drive our AI features are reviewable and versioned. Not a black box.
Every AI call is logged with prompt, response, token counts, and cost. Queryable for debugging or audit.
AI spend per organization is tracked. We can answer "how much did AI cost us last month?" with numbers.