Sixteen decisions your company is making with scattered signal.

Industry research says 70 percent of role moves should be internal. At most Fortune 500 companies the actual rate is 30 to 40 percent. The gap is not a culture problem. It is a visibility problem. No one inside the company can see who already on payroll matches the open role because the matching signal is scattered across HRIS, performance, project allocation, learning, and Slack.

NODES continuously scores every employee against every open role across the company. Reads current-role fit decay (someone who has outgrown their seat), target-role fit (someone whose pattern matches an open posting), and long-arc trajectory. Surfaces matches the org chart hides. The mobility workflow opens with employee opt-in. Manager mediates. Decision Trace logs the reasoning.

Modeled expectation: $400K to $900K of annual production unlocked per internal reassignment, based on saved external recruiter fees and ramp time.

45-day pilot on one business unit with 500+ employees. Money-back outcome: at least 10 high-confidence mobility matches surfaced with Decision Traces, or refund.

Senior leaders leave. At most Fortune 500 companies, the bench depth on critical role families gets reviewed annually, sometimes quarterly, never continuously. By the time a head of underwriting or a regional president announces departure, the replacement scramble takes 60 to 90 days at minimum. The cost is not the search fee. The cost is the discontinuity in the team they were leading.

NODES reads the senior leader signal pattern continuously. Identifies ready-now and ready-soon successors across the org against the calibrated role-family pattern. Refreshes the readiness bands monthly. Drafts the development plan for each named successor with the specific skills, stretch assignments, and exposure they need to be ready in 6, 12, or 24 months.

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

60-day pilot scoped to one role family (e.g, regional VPs, senior engineering managers, head underwriters). Money-back outcome: deliver named successors with Decision Traces or refund.

At every Fortune 500, two managers in the same role family with comparable team composition retain at meaningfully different rates. Sometimes 88 percent versus 64 percent over 12 months. Most companies do not surface this variance until exit interviews from the low-retention team start piling up. By then the cost has been paid.

NODES reads manager-team data continuously. Tenure, retention rate, team performance, internal mobility, ramp curves of new hires under each manager. Flags variance outside the role family’s typical band, sustained across two consecutive quarters. Drafts the coaching workflow with the specific behavioral pattern that needs intervention. Your HRBP approves and runs the conversation.

Modeled expectation: $420K to $680K of attrition cost recovered per manager pair where the variance closes within two quarters, based on historical attrition costs.

45-day pilot scoped to one function (e.g, field sales managers, engineering managers). Money-back outcome: surface 3+ variance manager pairs with Decision Traces or refund.

Top performers signal departure for six to nine months before they resign. The signals are real and consistent: reduced calendar load, drop in cross-team meetings, decreased Slack channel diversity, changed LinkedIn activity, fewer commits if engineering, fewer closed deals if sales. Nobody is reading the signal stream together. By the time the resignation hits, the window for intervention has closed.

NODES reads the continuous fit pattern against historical-departure signatures from prior exits at your company. Flags cohorts entering the high-risk pattern with a six-week intervention window. Drafts the retention investment workflow: who, what conversation, what offer or development opportunity, who approves. Manager runs the conversation.

Modeled expectation: $1.8M to $2.4M of cohort attrition cost avoided per six-week intervention on a 22-person cohort, based on historical-departure pattern matches.

60-day pilot on a defined role family or business unit. Money-back outcome: identify named retention cohort with Decision Traces and run at least one intervention workflow, or refund.

Your HR team has answered the same parental-leave question 14 times this year. Average HR ticket cycle time at most Fortune 500s sits at three to five days. The policy library is searchable but not legible. Your HRBPs spend a third of their week on questions a well-written agent could draft in a minute.

NODES reads incoming HR tickets via your existing ticketing system (ServiceNow, Zendesk, Jira Service Desk, Freshservice). Classifies each ticket against HRIS context. Drafts the answer with the right policy clause cited, the right approver tagged, in the right tone for that employee. Your HRBP one-clicks approve in the UI they already know. The Decision Trace logs the reasoning for every drafted response.

Pilot target: 30 percent reduction in HR ticket cycle time and 25 percent auto-resolution on policy-lookup tickets, written into the pilot agreement; miss the threshold and the refund clause applies.

60-day pilot scoped to one business unit. Runs alongside your existing ServiceNow or equivalent. Money-back outcome: hit the 30 percent cycle-time reduction and 25 percent auto-resolution rate, or refund.

At most Fortune 500 companies, headcount forecasting lives in a finance spreadsheet. The spreadsheet does not read ramp time, attrition curves, pipeline velocity, or role-family hiring difficulty. The finance team estimates. The people team disagrees. The plan is wrong by month six. The board sees the variance.

NODES reads HRIS attrition curves, ATS pipeline velocity, ramp curves by role family, role-family comp benchmarks, and your business plan inputs. Models next 12 months of headcount need by role family with backfill cost and ramp drag baked in. Updates monthly as new outcomes come in. Replaces or augments the finance spreadsheet with people-data-native forecasting.

Pilot target: Deliver forecast accuracy that beats current finance-spreadsheet methods on the 90-day window, as defined in the pilot agreement. The model provides continuous updates, not just annual.

60-day pilot benchmarked against the current finance forecast for the same window. Money-back outcome: beat the spreadsheet’s accuracy on the 90-day window or refund.

Comp decisions drift from market between annual cycles. Off-cycle exceptions accumulate without defensible justification. Manager comp recommendations get rubber-stamped because there is no rigorous way to evaluate them. Pay equity exposure compounds.

NODES drafts every comp decision with a Decision Trace citing the market data, the performance data, the retention risk, and the role-family band. Flags band drift as it happens. Runs continuous pay equity monitoring across protected classes. Surfaces manager-by-manager comp-versus-retention curves so the conversation moves from gut feel to data.

Pilot target: Deliver audit-grade evidence on every comp decision and surface manager-by-manager curves with statistically defensible findings.

45-day pilot scoped to one function or one annual merit cycle. Money-back outcome: deliver a defensible audit on the last 12 months of comp decisions with named findings, or refund.

ER cases take weeks to document. Decision Traces on adverse actions (termination, demotion, comp reduction) live in fragmented case notes across email, HRIS, and ER case tools. When litigation hits, the defensible audit trail has to be reconstructed from memory. Litigation exposure compounds quietly.

NODES handles case intake automation, drafts the documentation, and generates a sha256-immutable Decision Trace for every adverse action. Surfaces cross-case patterns (Title VII exposure, retaliation signals, manager-level case clustering). Adverse-action floor is architecturally locked, no autonomy level can authorize an adverse action without a human approver. That guarantee is the GC’s procurement argument.

Pilot target: Generate an audit-grade, sha256-immutable evidence chain for every adverse action, designed to be court-defensible.

60-day pilot scoped to ER cases in one region. Money-back outcome: deliver Decision Traces on every adverse action in the pilot window with documented methodology, or refund.

4/5ths parity gets audited quarterly. By the time a violation surfaces, the cohort is already locked in and the regulatory exposure has been incurred. Most DEI tools dashboard the past. Few catch the drift before it crystallizes.

NODES runs real-time 4/5ths parity monitoring across every hiring cohort, every promotion cycle, every comp decision. Flags drift before it crystallizes. Produces named manager-by-manager retention gap analysis. Runs label triangulation when manager-rating signal disagrees with output signal. The inverse-keyword filter (the screening rules that filter out protected-class proxies) gets surfaced as an inert weight on every Decision Trace.

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

60-day pilot on one function or one hiring cohort. Money-back outcome: deliver continuous monitoring dashboard with named findings or refund.

EU AI Act high-risk obligations live August 2026. NYC Local Law 144 is active. Mobley v. Workday is moving through federal court. Every Fortune 500 GC needs a defensible audit posture for every AI system in the company, not just the AI hiring tool. OneTrust and Drata do not do model-level audit. Your existing AI vendors ship a score and ask for trust.

NODES produces a sha256-immutable Decision Trace for every AI-assisted decision, with bias check, methodology, stress test, and comparable historical outcomes included. Sold as an overlay for your existing AI vendors (Workday, Eightfold, HireVue, ServiceNow) too, not just for NODES decisions. Inventories your AI stack against EU AI Act risk tiers. Produces the audit packet your GC and your board need.

Pilot target: Produce a sha256-immutable audit trail for every AI-assisted decision. The system includes an architecturally locked adverse-action floor, where the validator rejects any save that violates it.

30-day pilot. Inventory your AI stack, classify under EU AI Act risk tiers, produce shadow Decision Traces on one high-risk system. Money-back outcome: surface defined audit coverage gaps on an existing vendor or refund.

Two reps in the same territory with the same comp plan close at 14 percent and 28 percent. Quota attainment varies within the same role across most enterprise sales orgs. The variance is not a coaching problem. It is a hiring and matching problem. The pattern of what made the top quartile produce was never captured, so it cannot be replicated.

NODES reads every signal across your CRM (call quality, deal velocity, account engagement), HRIS (tenure, comp, ramp), performance database (quota attainment, pipeline coverage), calendar (account meeting cadence), and territory data. Scores every current rep against the top-performer pattern. Scores every new hire against the same pattern. Drafts the next coaching action for the bottom quartile.

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.

45-day pilot scoped to one sales segment. Money-back outcome: predicted top quartile outperforms predicted bottom quartile by 25 percent+ on quota attainment, or refund.

Churn surfaces 30 to 60 days too late. CSM-to-account matching is gut feel. Expansion opportunities sit in the data unread. Gainsight aged. The market for continuous account health that actually predicts is open.

NODES reads account activity in CRM, support ticket volume and sentiment, call transcripts, product telemetry where available, and CSM tenure and pattern data. Scores account health continuously. Flags churn risk 60 to 90 days earlier than current methods. Surfaces expansion opportunities ranked by signal strength. Drafts the next outreach.

Pilot target: Flag predicted churn 60 to 90 days earlier than current methods. This was achieved on the held-out test set and is the basis for the pilot agreement.

45-day pilot scoped to top 200 accounts. Money-back outcome: prediction accuracy beats current method on held-out test, or refund.

Deals slip from week three to week six because the early signals (missing exec sponsor, email cadence shift, calendar pattern change, single-thread risk) are not being read together. Forecast accuracy degrades. The exec team learns about the slip when the quarter closes.

NODES reads the deal signal stream across CRM, calendar, and email metadata. Compares the signature against prior deals that slipped at this stage. Drafts the recovery play: the missing exec to bring in, the talking points, the timing. Your CRO or VP Sales approves before the deal slips a second time.

Pilot target: 25 percent reduction in deal slippage rate on the pilot segment, based on models of prior slippage patterns. This target is written into the pilot agreement.

45-day pilot scoped to deals over $250K ACV in one segment. Money-back outcome: identify and flag at least 80 percent of deals that slipped in the pilot window or refund.

New reps take 8 to 12 months to ramp at most enterprise sales orgs. The pattern of what got the top-quartile reps to productivity fast was never captured. Sales enablement runs the same onboarding for everyone. Outcomes vary 2x or more.

NODES reads ramp signals across CRM (early deal activity, call ratings, pipeline build), calendar (meeting cadence with manager, with peers, with customers), and learning system completion. Compares each new rep to the trajectory of top-quartile reps in the same segment. Drafts the coaching intervention (peer pairing, manager 1:1 script, specific call rehearsal). Manager approves.

Pilot target: 31-day ramp acceleration per rep paired with the buddy pattern, as validated on pilot cohort data. The money-back agreement is for a median acceleration of 10+ days.

60-day pilot on a new-rep cohort. Money-back outcome: median ramp acceleration of 10+ days versus the unpaired baseline, or refund.