Make workforce decisions with Talent Intelligence you can trust

Talent Markets

Skills Graph

Workforce Planning

Pay Benchmarks

Talent Risk

Circular diagram showing Talent Market Intelligence modules including Supply and Demand, Compensation Intelligence, Brand Intelligence, Location Analysis, Skills Growth and Insights and plus 42% GenAI Skill Growth
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Collabera company logo
Galent company logo
TeamLease Digital company logo
MMG Make My Garden company logo
abilityaudit.ai company logo
InfoDyne company logo
Quess company logo
Collabera company logo
Galent company logo
TeamLease Digital company logo
MMG Make My Garden company logo
abilityaudit.ai company logo
InfoDyne company logo
Quess company logo
Collabera company logo
Galent company logo
TeamLease Digital company logo
MMG Make My Garden company logo
abilityaudit.ai company logo
InfoDyne company logo

80% less guesswork, 3X Higher Decision Confidence

80%

Less Guesswork

Replace assumption with real-time talent market intelligence.

2X

Better Talent Targeting

Identify the right talent pools & source faster.

35%

Earlier Market Visibility

Spot emerging talent & skill shifts before they impact hiring.

40%

Faster Workforce Decisions

Make faster workforce decisions with stronger market evidence.

25%

Lower Hiring Cost

Benchmark compensation & reduce unnecessary hiring overspend

2X


Better Location Decisions

Compare talent markets & choose locations with greater confidence

The talent intelligence layer behind every hiring decision

How much talent is available, and where can you find it? 

Total talent available for the role

Talent availability by skills, experience, and location

Where talent is currently employed

Cities with the highest talent concentration

Active vs. passive talent availability

Supply overview map for Forward Deployed Engineer across India showing 4,550 matched candidates, 62 average days to hire, active supply of 484 profiles, passive supply of 1,716 profiles, and diversity representation of 86% male and 14% female
Supply expansion funnel for Forward Deployed Engineer showing addressable supply widening from 2,200 direct matches to 44,000 through adjacent role, applied AI, and relaxed match expansion
Supply distribution for Forward Deployed Engineer showing total addressable supply of 2,200 with experience split across 0 to 12 plus years and top cities led by Bengaluru at 36%, Hyderabad at 15%, and Pune at 13%

Who else is hiring for this role? How fast is demand moving?

Live  job posting volume by role and market

Hiring velocity and demand trend over time

View competitor hiring patterns by function, backed by historical data.

Emerging roles and skill demand shifts

Hiring demand trend chart for AI Platform Engineer from July 2025 to December 2026 showing annual demand of 38,000 with forecast growth of 18% and projected rise to 44,840 by December 2026
Demand composition donut chart showing total demand of 38,000 by experience band with 5 to 8 years at 34% and most in-demand skill clusters as MLOps, LLMOps, Cloud Platforms and GenAI and LLM Integration
Market demand distribution showing 38,000 total demand by location with Bengaluru at 36%, Hyderabad at 22%, Delhi NCR at 18%, and by employer type with GCCs at 47% and IT services at 30%

What does the market pay?
How fast is it hiring?

Compensation ranges by role, level, and market

Competitor salary benchmarking

Compare talent costs across Tier 1, Tier2, & regional talent markets

Hiring Budget forecasts & planning scenarios

Indian market compensation range for Forward Deployed Engineer with 4 to 8 years experience showing total cash range of 34L to 72L, market median at 50L, and salary by experience band from 28L at 0 to 2 years to 90L at 10 plus years
Employer premium analysis showing AI hiring growth by sector with frontier labs at 48%, product companies at 42%, enterprise SaaS at 36%, and cloud and data platforms at 28% above IT services baseline
Offer score output for candidate Namita Kukreja showing AI recommendation of 62L at P75, with capability scores of 96% extreme for enterprise AI deployment, 92% extreme for AI solution architecture, and 90% high for product engineering
Compsense AI salary intelligence interface showing natural language salary query for roles including FDE in Bengaluru, senior product designer in Mumbai, and engineering manager, with filters for GenAI, LLMOps, Cloud and Customer Integration

Which market gives you the best talent-to-cost ratio?

Side-by-side comparison across cities and regions

Talent supply and cost indexed by location

Time-to-hire benchmarks by market

Site selection scorecards for GCC and expansion planning

Sankey flow chart showing talent mobility for Forward Deployed Engineer with 136 relocation-ready candidates and 28% of active talent open to relocate, with Hyderabad and Pune as strongest feeder markets to Bengaluru
Bar chart showing talent relocation rates for Pune 120%, Hyderabad 112% and Bengaluru 120%
India talent map showing Forward Deployed Engineer supply by city with Hyderabad at 15%, Pune at 13.4%, Delhi NCR at 11%, Chennai at 8%, and Mumbai at 6% with salary ranges per location

What skills define this role today, and what skills will matter next?

See the most important skills defining the role today

Understand how the role is evolving over time

Spot emerging skills and those becoming less relevant

Identify adjacent skills and roles to expand your talent pool

Determine whether to build, borrow or buy talent based on skill availability, market maturity, & business needs

Emerging high growth roles showing AI Solutions Engineer up 145%, Customer AI Engineer up 118%, Applied AI Engineer up 94%, Prompt Engineer up 88%, and AI Security Engineer up 80%
Skill lifecycle chart categorising AI Agents, MCP and RAG as emerging, AI Solutions and Customer AI Engineer as growing, DevOps and Data Engineer as mainstream, and Selenium QA and Manual Testing as declining
UI diagram showing five workforce strategy options including Build Internal Capability, Invest in Future Skills, Borrow Specialist Expertise, Buy Strategic Leadership and Sunset Declining Roles
Build, borrow, buy and bridge strategy table for AI roles showing FDE and AI Solution Engineer as build, LLMOps Engineer as borrow, AI Architect and AI Research Scientist as buy, and Customer AI Engineer as build

Compare employer brand performance across competitors

Track candidate sentiment, reviews, and reputation signals

Benchmark talent mindshare and employer attractiveness

Identify competitor strengths, weaknesses, and hiring advantages

Turn competitive brand insights into better talent attraction strategies

Positive and negative sentiment trend charts from January to June showing Competitor A at 69% positive and 10% negative, Competitor B at 54% positive and 19% negative
Employer brand overview showing 1.86M total mentions, 5.53M engagements, 294.7K unique users, net sentiment index of 40, and share of voice at 22.8%
Radar chart comparing employer brand scores across three companies showing your brand at 7.5, Competitor A at 7.1, and Competitor B at 6.8

Supply Overview

Supply Expansion

Supply Distribution

Supply

Hiring Demand Overview

Demand Composition

Market Demand Distribution

Demand

Compensation Benchmark

Employer Premium Analysis

Offer Scorer

Compsense.ai

Compensation

Talent Mobility

Talent Distribution

Hiring Recommendation

Location Analysis

Role Evolution

Skills Intelligence

AI Workforce Recommendation

Build+Borrow+Buy Strategy

Skills & Role Intelligence

Sentiment Overview

Executive Summary

Competitive Benchmark

Brand Insights

Office with employees working on computers

Built on trusted data. Designed for impact.

Powering talent and market intelligence with scale, accuracy, and ethical data practices

82%

Addressable workforce covered, India + USA + Europe

 100k+

Role and title variants normalized

 8M+

Live roles under continuous observation

 6yrs

Historical demand data across both markets

140+

Structured signals per individual

 90%+

Profile with verified role and skills

 60K+

 Skills mapped into a dynamic, market-aligned ontology

 350M+

Professional profiles resolved into distinct, research-ready talent identities

The most dependable, auditable, 
verifiable talent intelligence data

Why leading enterprises choose HireSense.ai

"HireSense.ai is a trusted partner for our GCC and IT talent strategy. Their clarity on where the market's headed helps us plan with precision. Value at every stage of hiring."

 Kapil Joshi

CEO — Quess IT Staffing

Kapil Joshi CEO at Quess IT Staffing

“HireSense.ai’s benchmarking data keeps our offers in India competitive & our decisions confident. A partnership that's genuinely strengthened our hiring.”

Aditya Mishra

CEO — CIEL HR

Aditya Mishra CEO at CIEL HR

"HireSense.ai's JD intelligence sharpens our hiring approach. Practical insights, data we can act on immediately."

Shailesh Singh

Regional Leader & VP – APAC – Cielo Talent

Shailesh Singh Regional Leader and VP APAC at Cielo Talent

"JD insights shape hiring at our GCC Tech Centre. Their data helps us craft roles that reflect the market, and it shows in candidate quality."

 Niloy Baksh

Head of TA — United Airlines, GCC Tech Centre

Niloy Baksh Head of TA at United Airlines GCC Tech Centre

“HireSense.ai has been a game-changer for our research and market intelligence - delivering in-depth, accurate reports at speed, and giving our leadership the clarity to make sharp calls in a fast-moving market.”

Sunil Nehra

Chief Executive Officer - FirstMeridian

Sunil Nehra Chief Executive Officer at FirstMeridian

"HireSense.ai is now integral to our talent function, giving us a clear, reliable view of ground reality that strengthens every client conversation. Real value, consistently delivered."

Sunil C

India Country Manager — Adecco

Sunil C India Country Manager at Adecco

"HireSense.ai's benchmarking drives our compensation strategy. Accurate, fast data. More confident conversations, with candidates and internally. Real value, consistently delivered."

Smitha S P

TA Head — CareStack

Smitha S P TA Head at CareStack

From strategic question to decision in days

HireSense.ai talent search input showing Data Engineering role scoped to Bangalore, Hyderabad, Pune and Chennai
Location comparison for Data Engineering talent across India with salary, availability and time to hire data by city
HireSense.ai recommendation output for Bangalore showing talent availability, salary benchmarks, headcount and budget guidance
1

Give us a hiring question.

Define the decision. GCC location. Compensation strategy. Engineering headcount. Competitor talent mapping.

HireSense.ai talent search input showing Data Engineering role scoped to Bangalore, Hyderabad, Pune and Chennai
2

Get decision-grade market intelligence.

Live platform data instantly. Analyst-delivered reports within 6 to 10 hours. Salary bands, talent supply, competitor hiring; current, not survey-based.

Location comparison for Data Engineering talent across India with salary, availability and time to hire data by city
3

Make the decision. Defend it.

Walk away with intelligence that is current at the time of the call and a documented basis for the decision when the board asks how you made it.

HireSense.ai recommendation output for Bangalore showing talent availability, salary benchmarks, headcount and budget guidance
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Things people ask before they say yes

Don't see your question, answered? Our team can provide personalized answers and guidance.

Contact Us

How accurate is your talent intelligence?

Accuracy is engineered into our data architecture. Multi-source market data is cleaned, deduplicated and mapped to proprietary taxonomies and ontologies covering roles, skills, capabilities, employers, seniority and locations. Context and proximity graphs then connect related signals, enabling more precise comparisons and inferences. Every insight is further strengthened through historical calibration, confidence scoring and expert talent-research validation.

Do you have historical data?

Yes. We maintain a historical talent intelligence graph that connects demand, supply, compensation, roles, skills, employers, sectors and locations over time. This enables us to track hiring momentum, skill shifts, emerging roles, capability build-outs and geographic movement—turning market snapshots into trends, forecasts and decision-ready intelligence.

Is your data AI-generated?

No. Our intelligence is built on real, multi-source talent-market data. A proprietary, custom-built, AI-orchestrated data infrastructure cleans and standardizes records, enriches context, and tags and classifies market signals at scale. AI makes the underlying data more consistent, connected and decision-ready—it does not create the numbers.

We already use a talent intelligence platform. Why should we use you?

Most talent intelligence platforms are designed to describe the market. We are built to help you decide.

Our practitioner- and consulting-led approach places every insight within your specific operating context—your roles, locations, competitors, hiring model and business priorities. Each output combines decision-grade evidence, confidence scoring and clear implications, making it easier to interpret and act on.

Our use cases are rooted in how talent decisions are actually made—from workforce and location strategy to hiring feasibility, compensation, competitive intelligence and fulfilment planning. The result is not more data, but greater confidence in the decision. 

What do we offer that Big Four firms cannot?

Decision-grade talent intelligence is a specialised data and research discipline—not simply a consulting exercise. It requires billions of data points across multiple sources and dimensions, a custom-built AI orchestration layer, contextual talent taxonomies and ontologies, and rigorously tested insight frameworks.

We combine this proprietary infrastructure with years of talent research consulting and a deep understanding of how workforce, hiring, location and compensation decisions are actually made. General advisory firms can provide broad strategic perspectives; we provide the specialist infrastructure, domain depth and practitioner context required to convert complex talent-market data into accurate, decision-ready intelligence