What does Talhive's approach to a composite score withthe evidence to defend it. look like?

Each dimension is scored 1 to 10 and labelled. The composite is a weighted average calibrated to what the specific role requires most. Pool rank tells you where this candidate sits relative to everyone assessed for the same mandate.

What does Talhive's approach to product judgment. not a process audit. look like?

Product assessment cannot be done through CV review alone. The dimensions that distinguish strong PMs, problem framing quality, prioritisation under constraint, how they work with engineering, require direct conversation and structured evidence-gathe

What does Talhive's approach to beyond the portfolio. look like?

Portfolio review reveals craft in controlled conditions. The design assessment framework tests the thinking, collaboration quality, and judgment that portfolios do not show, the dimensions that determine whether a designer is effective inside a real

Pre-hire assessment · Executive screening

Candidate Assessment & Intelligence.

Most shortlists are formatted CVs with a summary call attached. Talhive's candidate assessment produces a written intelligence brief for every shortlisted candidate: competency evidence, motivation analysis, risk flags, and a pool rank, before the first interview.

The brief does not begin with the candidate. It begins with the role. The brief determines the scoring criteria. The criteria determine the evidence we gather. The evidence goes into writing before any recommendation is made.

What you receive

Five sections. Every shortlisted candidate.

Every section is written against the specific role brief, not a generic template. Gaps that matter are named. If a dimension cannot be verified, it is marked as unverifiable, not estimated.

01

Candidate Snapshot

Verified profile: role, years of experience, education, archetype, and composite score at a glance.

02

Verified Skills Profile

Competency assessment with evidence and verdict for every dimension. No unsubstantiated ratings.

03

Culture Fit Fingerprint

Scored against the client's specific cultural criteria, not generic proxies or personality type labels.

04

Value Projection Brief

12-month milestone-specific impact hypothesis built from comparable career evidence.

05

Competitive Risk Assessment

Competing offers, urgency signals, and a recommended closing strategy specific to this candidate.

Scoring

A composite score with the evidence to defend it.

Each dimension is scored 1 to 10 and labelled. The composite is a weighted average calibrated to what the specific role requires most.

Strong Match

8-10

Evidence is clear, specific, and verifiable. Dimension met or exceeded.

Match

6-7

Solid evidence. Meets the requirement without exceptional signal.

Partial

4-5

Evidence present but incomplete. Named gap noted with impact level.

Gap

1-3

Evidence does not support the dimension. Coaching note included.

Assessment frameworks

Three practice areas. Each with its own dimensions.

Assessment criteria are calibrated to the practice area. An engineering assessment and a product assessment test for fundamentally different things.

Engineering & AI

Product

Design

Technical competency with production evidence.

The engineering assessment framework is built around what candidates have shipped in production, not what they can articulate in a whiteboard session.

Hands-On Execution

Production code shipped, features owned end-to-end. This is the gate dimension. A candidate who cannot demonstrate production-grade work does not clear the gate.

System Design & Architecture

Clarity of architectural decisions, scalability judgment, trade-off reasoning. Evidence from specific products built.

App / Platform Ownership

Evidence of owning a significant technical surface end-to-end. Metrics: MAU, DAU, transaction volume.

Stack Depth & Currency

Verified proficiency in the specific stack the role requires. Self-reported skills tested against career evidence.

Performance & Reliability

Production evidence: crash rates, latency, ANR reduction, uptime. Inference is not accepted.

AI / ML Signal

For AI/ML roles: production deployment evidence, model evaluation rigour, research vs production distinction.

Testing & Discipline

TDD evidence, coverage targets, CI/CD ownership, code review rigour. Engineering culture signal.

Leadership & Mentorship

Direct evidence of raising team quality: hiring, coaching, code review culture, technical decision-making.

Product Thinking

Engineering decisions aligned to product and user outcomes. Weighted for founding and mobile roles.

Domain Relevance

Prior domain experience relevance. Assessed as signal, not gate, unless brief makes domain mandatory.

Product judgment. Not a process audit.

The dimensions that distinguish strong PMs require direct conversation and structured evidence-gathering, not CV review.

Product Judgment

Quality of decision-making under ambiguity and constraint. Specific examples of hard calls made.

Problem Framing

Ability to define the right problem before jumping to solution. Evidence of changing direction after reframing.

Prioritisation Quality

Hard tradeoffs made under constraint. Features not built, scope deliberately cut, conflicts resolved.

Metrics Fluency

Signal metrics vs vanity metrics. Evidence from actual measurement decisions in prior roles.

Execution with Engineering

How they handle pushback, resolve spec ambiguity, and manage the engineering relationship under pressure.

Roadmap Ownership

Strategic clarity, stakeholder buy-in, horizon balance. Assessed through specific roadmaps owned.

Zero-to-One vs Scale Fit

Context fit: builder vs operator, early vs growth vs mature. Mismatched context is a common failure mode.

Beyond the portfolio.

Portfolio review reveals craft in controlled conditions. The design assessment tests thinking, collaboration, and judgment that portfolios do not show.

Product Thinking

Does design connect to user and business outcomes, or stop at visual quality?

Interaction Quality

State management, edge cases, error handling, micro-interactions. Specific design decisions assessed.

Systems Thinking

Design consistency, component reuse, scale. Design systems contribution or creation evidence.

Visual Craft

Quality and intentionality of visual execution. Calibrated relative to role context.

Collaboration with PM & Eng

How the designer handles scope constraints, technical pushback, and design review with non-designers.

Speed vs Polish Judgment

Can they distinguish contexts requiring craft from contexts requiring iteration? Strong maturity signal.

The Sample Candidate Intelligence Dossier

Senior Android Engineer, Series B Product Company, Bengaluru. Open case study showing the full engineering assessment format: 12 dimensions, composite score 8.1/10, pool rank, culture fit fingerprint, 12-month value projection, and closing strategy.

Request the sample brief →

8.1/10

Composite score

12

Dimensions

5

Sections

Request a sample brief → See case studies →