Turn fragmented enterprise data into agent-built, human-approved workflows across systems.

Problem: 1,000+ applicants per role, screened by keyword filters that reject 80 percent of future top performers. Structured interviews take 45 minutes per candidate. Hiring managers skip them or conduct them inconsistently.

Solution: The brain reads every applicant against 28+ behavioral dimensions calibrated on your own production data. A 0-100 Fit Score writes back into your ATS as a native field, so your recruiters never leave the screen they already work in. A 12-minute async interview surfaces the same signals, scored on the same structured rubric for every candidate. Candidates are told it is AI-assisted, and every score carries a Decision Trace. Outcomes are monitored continuously for adverse impact, with the four-fifths ratio as one screen among validity evidence. No candidate is advanced or rejected on the AI score alone. The brain identifies passive candidates from public professional profiles using patterns learned from your own validated top performers, with notice and consent flows configured to your counsel's requirements. We connect to Workday, SAP SuccessFactors, Greenhouse, iCIMS, Avature, and Taleo through your existing auth, scoped to least privilege.

Proof: 80 percent of top performers at a Fortune 500 carrier were filtered out by a single "relevant industry experience" requirement. The Fit Score caught them.

Proof: Four of six top-performer signals detected in a candidate the ATS would have rejected. That candidate was promoted at month 11.

Problem: New hires take 6-9 months to reach full productivity. Managers rely on gut feel to decide who needs coaching.

Solution: The brain reads onboarding signals (training completion, early production, manager check-ins) and flags exactly where each new hire is diverging from the top-performer ramp curve.

Pilot observation: Role-calibrated ramp signals identified at-risk hires 6 weeks earlier than manager escalation at pilot scale.

Problem: High performers leave because they do not see a path. Career development conversations happen once a year, and employees leave when they cannot see what is next.

Solution: The brain scores every employee against every open or projected role using the same Fit Score, surfacing the highest-fit next moves and the gaps to close. Cross-role pattern matching replaces manager nominations.

Modeled: Internal mobility candidates matched the top-performer pattern for the target role at rates comparable to external hires scored by the same model.

Problem: Succession plans live in spreadsheets updated once a year. When a senior leader announces departure, the replacement scramble takes 60 to 90 days at minimum.

Solution: The brain reads the senior-leader signal pattern continuously, identifies ready-now and ready-soon successors against the calibrated role-family pattern, and drafts the development plan for each named successor.

Pilot target: Deliver readiness scorecards on every critical role family, where each ranking carries an audit-grade Decision Trace defensible against challenge.

Problem: The best managers consistently develop top performers. Others struggle to, and the difference is rarely visible early enough to coach it.

Solution: The brain traces team-level production, ramp curves, and retention rates back to coachable patterns. The result is a private coaching signal, surfaced only to the manager and their HRBP. We never publish a ranking.

Pilot observation: Manager-level production traces revealed a 2.1x output variance attributable to management patterns, controlling for hire quality.

Problem: A single mis-hire runs one to two times annual salary in fully loaded cost. By the time HR sees an exit interview, the decision was made months ago.

Solution: The brain reads production trends, engagement signals, and cohort patterns to surface retention risk before the employee starts job-searching.

Modeled: cohort-level attrition forecast within 3 percentage points of actual on the study population.

Problem: Your HR team answers the same fourteen questions every week. Each answer takes 8-12 minutes and a policy lookup.

Solution: The brain reads every inbound ticket, drafts a policy-grounded response, and routes edge cases to the right specialist. The human approves, and the system learns.

Pilot target: 30 percent reduction in ticket resolution time for queues where answers take 8-12 minutes, with zero policy-violation escalations on auto-drafted responses.

Problem: Headcount planning runs on last year's numbers plus a growth target. Nobody models what the incoming cohort will actually produce.

Solution: The brain projects cohort-level output by combining pipeline quality scores, historical ramp curves, and attrition forecasts into a single planning model. The brain matches candidate patterns to geo-calibrated production data, recommending the placement most likely to produce sustained output.

Pilot target: Cohort output forecast within 8 percent of actual over a 12-month window at 2,000-hire volume.

Problem: Compensation bands are set by title and tenure. Actual production varies 5x within the same band.

Solution: The brain shows where pay has drifted away from contribution and surfaces pay-equity gaps, so comp conversations start from evidence instead of title and tenure alone. Your team owns every pay decision.

Proof: Top-performer rate rises monotonically by score quintile: RPA 5.1% (Q1) to 13.0% (Q5), 2.55x. n=747, out-of-sample.

Problem: ER cases take weeks to document, and the evidence for adverse actions lives in fragmented case notes across email, HRIS, and ER case tools. When litigation hits, the audit trail has to be reconstructed from memory.

Solution: The brain handles case intake, drafts the documentation, and generates a sha256-immutable Decision Trace for every adverse action. No autonomy level can authorize an adverse action without a human approver.

Pilot target: Generate an audit-grade, sha256-immutable evidence chain for every adverse action.

Problem: Four-fifths parity gets audited quarterly. By the time a violation surfaces, the cohort is already locked in and the regulatory exposure has been incurred.

Solution: The brain runs real-time four-fifths parity monitoring across every hiring cohort, every promotion cycle, and every comp decision, and flags drift before it crystallizes.

Pilot target: Provide continuous monitoring across every hiring cohort, promotion cycle, and comp decision, delivering live ratios instead of quarterly snapshots.

Problem: Audit prep takes weeks of pulling records across five systems. Evidence gaps surface during the audit, not before.

Solution: Decision Traces provide a continuous, queryable audit trail. Every hiring decision, every score, every override is linked to its evidence chain and signed.

Pilot target: An audit query that runs in minutes instead of a multi-week records pull, with every score resolving to a signed, immutable Decision Trace.

Problem: Two reps in the same territory with the same comp plan close at 14 percent and 28 percent. The pattern of what made the top quartile produce was never captured, so it cannot be replicated.

Solution: The brain reads CRM, HRIS, and performance data to score every current rep and every new hire against the top-performer pattern, and drafts the next coaching action for the bottom quartile. The brain identifies which employees are most likely to refer a top performer, based on network overlap with the validated top-performer pattern.

Pilot target: Predicted top quartile of reps will outperform the predicted bottom quartile by 25 percent or more on quota attainment. The model is based on patterns from four years of production data from the insurance deployment, adapted for sales roles.

Problem: Customer churn is measured after it happens. Renewal conversations start too late and rely on relationship intuition.

Solution: The brain reads usage patterns, support ticket sentiment, and engagement signals to score renewal risk months before the contract date.

Pilot target: Flag 70 percent of eventual churns with renewal risk scores at least 90 days before contract expiration.

Problem: Deals slip a week at a time. By the time the forecast misses, the quarter is over.

Solution: The brain reads CRM activity, email cadence, and meeting patterns to score deal health in real time. Slipping deals surface before the rep flags them.

Pilot target: Identify at-risk opportunities 3 weeks earlier than rep self-reporting, via deal-health scoring in a CRM integration.

Problem: New reps take 8 to 12 months to ramp. The pattern of what got the top-quartile reps to productivity fast was never captured, so enablement runs the same onboarding for everyone.

Solution: The brain reads ramp signals across CRM, calendar, and learning-system completion, compares each new rep to the trajectory of top-quartile reps in the same segment, and drafts the coaching intervention. The manager approves.

Pilot target: 31-day median ramp acceleration for reps paired with the buddy pattern. The money-back agreement is for a median acceleration of 10+ days.