What is Talentprism?
It’s a collection of software tools for staffing companies for quickly finding qualified and interested candidates for their jobs from their database or sourced leads.
In short term, it operates at 2 critical phases of recruiting cycle
- Given a job order, our matching algorithm can find and rank candidate profiles based on multiple critiria
- Candidate-facing agents can talk to job seekers to help find jobs, evaluate eligibility and save valuable profile information.
In longer term, it helps firms build an active talent pool with higher quality contact and preference data, thus building a proprietary data asset in an increasing AI-lead era of software democratization.
Who is the target market?
Staffing companies in skilled trades in the US focused on industrial, manufacturing and shipbuilding industries.
What pain point does it solve?
Recruiters often face a cold-start problem with distinguishing between qualified and interested candidates vs the rest. Top of funnel candidate sourcing is often high volume. Internal database is often polluted with outdated information, and thus, not well utlized. Resort to spending lot of money on ads for sourcing leads. Recruiters follow very manual processes only follow up days later - and in most cases manually have to log interactions into their ATS.
This is inefficient and ineffective.
How does it solve these pain points?
Most recruiting operations are algorithmic, and better handled by software. If done well, will allow recuriters to focus on building better relatioships with qualified candidates.
Talentprism can
- Keep log of candidate contact status
- Track preferences like role, location, rate etc
- Match job descriptions to candidates objectively
- SMS campaigns
- talk to candidates and screen them
- enrich profiles through conversations and collect applications or referrals
These are all software problems, and Talentprism tackles them. Recruiters can then follow-up with qualified and interested candidates.
What this market?
Heavy indsutries, like shipbuilding, employ a high fraction of contract labour and rely on staffing firms to fill workforce needs, often on short notice and with strict qualification critiria. Staffing firms have to act quickly in finding candidates from the limited talent pool. The following combination of factors make this the right target market -
- Time-to-submit is north star metric, easy to measure and demonstrate value
- firms value candidate data, enabling better data capture builds their talent pool
- contract labour is cyclical - good data hygiene will create compounding outcomes
- ai chatbots via sms and phone lend well to this demographic
- the industry is gnerally lagging in tech, so high impact potential
- resilient to AI disruptions
How is different than status quo?
It rapidly accelerates the process by enabling prioritization of right candidates.
What is the integration cost to start using Talentprism? i.e. what is the friction?
To run outbound campaigns, Talentprism needs access to the candidate profiles from an agency database. For other features like phone campaigns, AI interviews, reminders automations, chatbot widget installation, there is minor devleopment effort on client systems.
What is the switching cost to cancel Talentprism once integrated? i.e. what is the moat?
Once Talentprism establishes personalized open channels of communication with a talent pool - companies value that highly and is very hard to replace a service. While all interactions and data collected is owned by the company, the personalization offered via AI agents is a key technilogical layer owned within talentprism.
How is it differnet than other AI recruiting companies?
Most AI recruting companies operate on targeting professional roles from public sources like linkedin profiles. In skilled trades, profiles are not on linkedin, and Talentprism instead focusses on building/maintaining agencies internal databases.
What are dogs not barking? i.e. what should work out in order for all this work out?
AI Memory - establishing long-lasting candidate conversation threads, as opposed to ephemeral transcational interactions. We want candidates returning to their personalized recruiter for new jobs, updates or sharing their preferences.
Eg: “let me know when X opens up, i need Y and Z” vs “not interested”