The TaaSFlow System
A proprietary recruiting system, run by expert operators.
TaaSFlow is software plus people. The system sources, researches, scores, and automates the mechanical work of hiring. Recruiters, sourcers, and researchers run the loop. Both parts are visible.
We don't wait for applicants.
The system reaches candidates across job boards, professional networks, communities, referrals, and our own talent memory in parallel. Every touch is logged, attributed, and measurable — reply rate, shortlist rate, hire rate per channel.
- Inbound + outbound in one funnel
- Channel attribution on every hire
- Past finalists resurfaced automatically
Context beyond the CV.
For each candidate the system pulls signal from public profiles, prior companies, project trails, and our internal history with them. Researchers verify the important claims before anything reaches a client.
- Public web enrichment (structured, sourced)
- Prior interactions and outcomes surfaced
- Every claim ties back to a source snippet
Evidence-first, per requirement.
Roles are decomposed into requirements. Each requirement is scored against explicit evidence — a CV quote, an answer, a verified fact. A single 0–100 fit score falls out of that math, not the other way around.
- Per-requirement verdict + evidence quote
- Coverage %, contradiction flags, engine version
- Same rubric applied to every candidate on a role
The boring, repeatable work runs itself.
Parsing, deduping, screening questions, status changes, notifications, handoffs, reminders, publish gates — automated with audit trails. Operators approve, override, and unblock; the system does the mechanical work in between.
- Publish gates and approvals
- Status transitions with audit rows
- Notifications and reminders on rails
Every claim shows its work.
Scores, insights, and shortlist recommendations link back to the exact CV excerpt, application answer, or research note that produced them. Contradictions get flagged, not hidden.
- CV excerpt viewer with requirement mapping
- Timeline of parsing, scoring, and decisions
- Downloadable evidence record for staff
You watch the pipeline move in real time.
Clients see the same board the platform runs on — no weekly PDF, no BCC threads. Kanban, decisions, offers, hire tracking, and pipeline activity all read from one system of record.
- Kanban + decision cockpit + offers board
- Realtime refresh across every surface
- One system of record for the whole hire
Humans decide. The system removes drag.
Recruiters, sourcers, and researchers run the accounts. The system automates parsing, scoring math, evidence linking, and audit logging so operators spend their time on judgment — outreach quality, calibration, client conversations, hiring decisions.
- Expert oversight owns calibration and escalation
- Researchers verify claims before shortlist
- Client success owns the relationship
What we do and don't claim
Serious system. Honest scope.
Parses, dedupes, structures evidence, scores against a shared rubric, runs the workflow, keeps the audit trail, and surfaces context — at a scale humans can't match.
Outreach voice, calibration on borderline candidates, client conversations, and the actual hire decision. We do not ship candidates unattended.
No fully autonomous AI recruiter. No black-box magic. No promises the system can't back with evidence and an audit row.
Hiring intelligence
Metrics that answer a question — or admit they cannot.
The workspace never draws a chart it does not have the data for. Below is the same component, showing a live number, a partial sample and an honest "not enough data" state.
Each metric answers one decision question — and says when it cannot
Time to first qualified candidate
How long until this role has someone worth a conversation?
4.2 days
median across 6 example roles
-4.9 daysvs previous example window (9.1 days)
- Role A3.1
- Role B4.2
- Role C5.8
- Role D9.4
View as table
| Item | Days to first qualified candidate | What it means |
|---|---|---|
| Role A | 3.1 | — |
| Role B | 4.2 | — |
| Role C | 5.8 | — |
| Role D | 9.4 | — |
Measured from the moment a blueprint is locked to the first evidence-backed candidate delivered for review.
Evidence coverage
How much of the scoring is backed by a quote from the source?
81%
of scored requirements carry a source quote
21 of 26 assessments have a verified quote attached.
Requirements without a quote are never counted as met — they surface for reviewer confirmation instead.
Review unverified evidence
5 assessments are waiting on a reviewer.
Where candidates drop out
Which stage is losing the people you want?
Fewer than 5 completed decisions in this example window.
Drop-out is only reported once there are enough decisions to be meaningful. Until then the product says so instead of drawing a chart.
See the system on your role
30-minute walkthrough on a live workspace.
We open the pipeline, the scoring rubric, the evidence record, and the audit trail — with a real role, not a demo.