AI question generation
Generate per-candidate question sets from a role blueprint and difficulty curve. Every item is reviewable and editable before it goes live.
Products — Assessment & hiring
The assessment and hiring-drive engine behind our recruitment work — AI-assisted question generation, a real coding environment, defensible proctoring, interview workflow and a report that arrives while the decision still matters.
01 — The problem
Eight hundred candidates arrive. Four rooms, one of which has no working projector. The assessment platform was tested on the office network, not the campus network, and it starts timing out at candidate two hundred. Someone begins writing names on paper.
The panel interviews until seven in the evening against a rubric that was agreed verbally that morning and interpreted differently by each interviewer. Shortlisting happens in a corridor conversation.
Three weeks later a spreadsheet arrives. By then two of the strongest candidates have accepted elsewhere, and nobody can reconstruct why candidate 412 was rejected.
None of this is a hiring problem. It is an operations problem, and it is entirely solvable with software plus people who have run drives before.
02 — The solution
One system holds registration, eligibility, assessment, proctoring, panel scheduling, rubric scoring and reporting. Because everything is in one place, the report is a query rather than a reconstruction — and it is available the moment the drive closes.
The assessment layer runs a real code execution environment against hidden test cases, so a coding round measures working code rather than syntax recall. Question sets are generated per candidate from a blueprint, which makes leaked papers largely worthless.
Proctoring produces evidence, not verdicts. The system flags what it observed; a human reviews every flag before it affects a candidate. Candidates are told in advance exactly what is monitored.
03 — Capabilities
9 capabilities, each of which exists because something specific went wrong without it.
Generate per-candidate question sets from a role blueprint and difficulty curve. Every item is reviewable and editable before it goes live.
Real execution across 14 languages against hidden test cases, with time and memory limits and partial scoring.
Tab-switch, face-absence and multi-face detection with a session recording. Flags are evidence for human review, never automatic disqualification.
Registration, eligibility rules, slot allocation, venue capacity and check-in — the logistics, handled.
Panel scheduling, structured rubrics, per-round scoring and written recommendations captured in the room rather than afterwards.
Full-fidelity practice runs for students on the real interface, so drive day is not their first encounter with it.
Per-candidate evidence, round-by-round scoring, funnel analytics and a shortlist you can act on immediately.
The assessment client buffers locally and syncs on reconnect. A network drop does not cost a candidate their attempt.
Push shortlists to your ATS, pull cohorts from LARE LMS, and wire the whole thing through the REST API.
04 — Dashboards
Each role sees the question it actually needs answered — not the same dashboard with rows hidden.
Create a drive, watch it run, decide from evidence.
Know what's coming, practise on the real thing, see where you stand.
The view your T&P cell has been building manually every placement season.
05 — How it runs
The same sequence every time, which is what makes the reporting a query rather than an archaeology project.
Role blueprint, eligibility rules and difficulty curve. The assessment is generated from this, not chosen from a catalogue.
The drive appears on the placement calendar; eligible students are notified and register in-platform.
Candidates practise on the exact interface, so drive day is about the questions rather than the software.
Per-candidate question set, real code execution, proctored session, local buffering against network loss.
Scores, submitted code and proctoring evidence in one view. Flags reviewed by a human before anyone is cut.
Panels scheduled automatically, scoring against the pre-agreed rubric, recommendations written in the room.
Company gets the shortlist and funnel. Institution gets participation and conversion. Students get their results.
06 — Why this one
Every feature exists because something went wrong on a real drive day. The offline buffering is there because a campus switch failed at candidate 200.
Flags are reviewed by humans and candidates are told in advance what is monitored. A drive that disqualifies people by algorithm will eventually be challenged, and should be.
Per-candidate generation from a blueprint means a leaked paper is worth very little, and difficulty stays comparable across candidates.
Because the data was structured during the drive rather than reconstructed after it, the report is a query. Speed here directly changes offer-acceptance rates.
07 — In production
08 — Pricing
Published figures are pending finalisation — request pricing and you'll get a real number against your actual cohort size, not a range.
One-off campus or walk-in drives.
₹—per drive
Organisations hiring continuously through the year.
₹—per year
Colleges running their own placement season on Drive.
Customper campus
Thirty minutes in a working environment with your scenario loaded. If it's a bad fit we'll tell you in the call rather than three emails later.