Every company has an Alex.

No. Hiring is where most companies start, because it's the fastest place to prove the pattern works against numbers you already track. The same brain runs across the rest of the talent lifecycle, your day-to-day operations, and your revenue systems. You don't have to turn it all on at once. Most companies prove it on hiring first, then expand to what's next once they trust the results.

No. Once we connect to your systems of record, NODES reads from them automatically. Your team doesn't need to feed data in. The brain learns continuously from what happens in the systems you already use. The only thing flowing in on your side is what you already have anyway: people getting hired, performing, getting promoted, leaving. We learn from that.

No. NODES handles the volume work: scoring, sourcing, initial screening, ranking. Your recruiters review the top of a pre-ranked queue instead of triaging hundreds of applications. They make every call about who moves forward. The system never auto-rejects anyone. It ranks, it explains, and humans decide.

It lives in your existing ATS. Your recruiters see scores inside the workflow they already use. We currently have native integrations with Avature, SAP SuccessFactors, Greenhouse, Workday, iCIMS, and Taleo. At the carrier in our case study, recruiters saw scores without ever leaving their ATS. Each connector uses your existing auth, OAuth or a scoped service account, is scoped to least privilege, runs entirely inside your environment, and is revoked the moment you disconnect it. Nothing is copied out. Other systems integrate the same way.

We can build a useful starting persona from a single top performer, and we're explicit that one person is just a starting point. The brain widens the pattern as more outcomes feed back, and the reasoning behind every score stays visible so you can see when it's leaning too hard on one example. You don't need years of clean history either. The Fortune 500 insurance carrier we work with launched on ATS data alone, and the Fit Scores sharpened measurably as performance outcomes fed back in.

Two architectural differences.

First, NODES deploys inside your VPC. The model is yours. Most other AI hiring tools either send your data through their servers or use one model trained on data from many companies at once. We do neither.

Second, every Fit Score is traceable back to the source data that produced it. There's no black box. If a score says someone is a strong match, you can see exactly why.

You pay for what you use. Pricing doesn't scale by headcount, so the whole organization can use the platform. Credits apply to screening, sourcing, AI interviews, and what happens after the hire. The numbers themselves are public: pilots start at $25K, the platform starts at $200K a year, and there is an outcome-based option priced at 2 percent of validated impact. We usually start with a paid pilot scoped to one motion, so you can prove results against the numbers you care about before moving to a full contract.

We monitor for bias in hiring outcomes continuously, and every Fit Score includes documented reasoning that can be audited. Protected and directly identifying attributes, like name, date of birth, race, gender, and age, are excluded from the features the model scores on, so a Fit Score reads what someone has done, never who they are on paper. We run adverse impact testing on outcomes and surface the results to your team, because a model trained on your own history can inherit your own history. Because the model is yours, it isn't pulling bias from a shared cross-customer dataset either. We work with your compliance team and any third-party auditor you bring. The system is designed for environments where every hiring decision has to be transparent and defensible.

Plan for weeks, not quarters. Because nothing leaves your environment, security and legal review tends to move fast: at the carrier in our case study it cleared in 17 days, the fastest AI vendor approval in their history, and they were in production 34 days after contract. Your timeline depends mostly on how quickly your team can grant sandbox access and confirm field mappings. For comparison, typical AI hiring vendor evaluations in regulated industries run six to twelve months and frequently never clear legal. The architecture is the reason.