Tell us about your team, your annual hiring, and your pipeline. We'll recommend the right tier and show your projected annual return on investment. The numbers below are filled in with an example to show you how it works — replace them with your own figures so your ROI is accurate.
Drag a slider to see how the headline responds under more conservative (or more aggressive) assumptions. These are display-only — your admin defaults aren't touched.
Value delivered month-by-month, broken down by source. The longer you use Staffility, the more your cumulative return adds up.
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Before the numbers, here is the plain-English version of what you are buying and how the pricing fits together. The recommendation and ROI on the pages above are built on top of this model.
Staffility is an AI-powered staffing and recruiting platform. It helps your back-office team move faster on the work that actually fills roles — searching your talent pool, reading and summarizing resumes, matching people to open jobs, and staying in touch with candidates you have worked with before. Your candidates and employees never need a login. You only pay for the staff working behind the scenes.
A license is for a fulfiller — the back-office staff who do the work: admins, business development, recruiters, and HR. Each license includes 2,500 AI assists per year, pooled and shared across your whole team. Licenses are tied to individuals but can be reassigned if someone leaves, and you can add extra licenses month-to-month for about $350 each. Every added license also adds to your shared assist pool.
An assist is a single AI-powered action. Most actions count as one assist; some may count as more. Assists are pooled and shared across all licenses in your tier, so your whole team draws from one bank. Actions that use an assist include running an AI-powered search (Now Assist), generating an AI summary of an uploaded resume (the upload itself does not use an assist), and AI parsing of jobs and resumes for job matching — the matching itself is algorithmic and does not consume an assist, only the AI parsing does.
Automated marketing to your candidate list is included in your subscription at no extra cost. The only assist cost is one assist to parse a candidate’s resume, and only after that candidate creates an account. Bulk-parsing large historical resume databases burns assists quickly — best practice is to parse only when a candidate is engaged or connected.
Staffility pricing is built on two things: the number of licenses your team needs and the number of AI assists you use each year. There are four standard tiers, with custom pricing available above Tier 4. Each tier bundles a set number of licenses and an annual assist allowance, and includes volume discounts — your cost per license drops as you grow. The recommendation on the pages above sizes your assist need from your team and hiring volume, then picks the lowest-cost tier that covers it.
Billing is monthly and recurring; you can prepay annually if you prefer. You can upgrade anytime during your year, prorated for the remaining months. Downgrades take effect at contract renewal.
Every assumption in the model above is anchored to industry benchmarks specific to Government Contracting IT & Technology firms. Here is the reasoning behind the four numbers that drive the result.
GovCon IT firms are labor-centric and earn revenue primarily from billable FTEs working under rate-based contracts (T&M, cost-plus, IDIQ labor ceilings). Industry benchmarks consistently place revenue per employee in the $200K–$300K range.
Typical math: fully-burdened billable rate $120–$150/hr × realized utilization ~1,700 hrs after PTO and overhead = ~$204K–$255K per billable FTE annually.
| Company type | Revenue per employee |
|---|---|
| Conservative GovCon IT | $200K |
| Typical / base case | $225K – $275K |
| High-performing / well-utilized | $300K+ |
We model at $250K because it is a neutral, defensible midpoint consistent with how large public GovCon IT firms and midsized primes price labor. It will not get challenged in a boardroom review. Sources: Deltek GovCon industry studies, SHRM/ANSI benchmarks.
The vacancy window is where the revenue loss actually compounds. Benchmarks vary materially by clearance status:
| Role type | Typical range | Conservative planning |
|---|---|---|
| Uncleared GovCon tech / IT | 45–75 days | 60 days |
| Active Secret | 60–90 days | 75 days |
| Active TS | 90–120 days | 105 days |
| TS/SCI (no poly) | 120–150 days | 135 days |
| TS/SCI + full-scope poly | 150–240+ days | 180 days |
U.S. commercial tech averages ~44–55 days. GovCon adds compliance reviews, slower offer approvals, and contract-alignment checks, which push uncleared roles ~10–20 days longer. Cleared talent firms report cleared cycle times running 2–3× longer than uncleared.
We model 60 days because it is accurate for uncleared roles, conservative for cleared roles, and defensible as a blended average for a general GovCon tech workforce. Many firms actually understate this number. Sources: SHRM/ANSI cost-per-hire studies, Deltek, cleared-talent staffing benchmarks.
SHRM reports a U.S. average cost-per-hire of ~$4,700 across all industries. That number mixes entry-level, hourly, and retail hiring, and doesn't reflect clearance, specialization, or billable tech labor. It is a floor, not a realistic number for GovCon tech roles.
| Role mix | Typical cost per hire |
|---|---|
| U.S. all-industry average (SHRM) | ~$4,700 |
| Technology roles | ~$6,000 – $9,000 |
| High-demand / specialized tech (cyber, cloud, DevOps, cleared IT) | > $10,000 |
| Agency or contingent recruiting | $12,000 – $20,000+ |
GovCon stacks additional structural cost drivers: smaller talent pools, clearance constraints, longer sourcing cycles, more recruiter time per hire, frequent use of specialized agencies, and contract-timing pressure that makes a bad hire far more expensive. Internal-recruiter shops still incur LinkedIn Recruiter, ATS, hiring-manager time, background checks, and rejection churn.
We model $10,000 as a conservative, defensible midpoint for GovCon technology roles. Sources: SHRM, LinkedIn Talent Insights, iCIMS, industry agency benchmarks 2024–2026.
Referral hires consistently outperform non-referral hires on retention across multiple independent studies. Typical findings:
| Source | Retention finding |
|---|---|
| Jobvite Recruiter Nation (multi-year) | Referrals retain 25–46% better at 1 year |
| SHRM employee-referral studies | ~46% retention > 1 year for referrals vs. 22% for job-board hires |
| LinkedIn Global Recruiting Trends | Referred employees are the #1 quality-of-hire signal |
We apply +30% as a relative lift to the baseline (70% × 1.30 = 91%), which is well inside the Jobvite and SHRM findings and below the midpoint of published ranges. Baseline retention, lift %, and days-to-fill are all editable by the admin so a customer's actual history can be substituted.