Topics
late
AI
Amazon
Image Credits:Bryce Durbin / TechCrunch
Apps
Biotech & Health
Climate
Cloud Computing
Department of Commerce
Crypto
Enterprise
EVs
Fintech
fund raise
gizmo
Gaming
Government & Policy
ironware
Layoffs
Media & Entertainment
Meta
Microsoft
Privacy
Robotics
surety
Social
Space
inauguration
TikTok
Transportation
Venture
More from TechCrunch
Events
Startup Battlefield
StrictlyVC
Podcasts
Videos
Partner Content
TechCrunch Brand Studio
Crunchboard
touch Us
Notable Silicon Valley startup acceleratorY Combinator held a Demo Day for its first Fall cohortthis week .
The 95 startup in this up-to-the-minute flock looked quite similar to recent YC age bracket in the mother wit thatit includes many AI startups . If I did my math rightfield , 87 % of the startups in this raft are AI companies . exchangeable to YC ’s summer and winter batches this class , there was a noticeable focal point on client - divine service - bear on AI and AI agents .
But among these , four company offend my interest , and they all had something in vernacular : They are building tools to help companies monitor their AI applications to quickly resolve or forbid inaccuracy , which is forbid more widespread borrowing of AI tool by endeavor . And enterprise companies should keep an oculus on them .
HumanLayer
What it does : API that enable AI agent to get hold of human being for help and favorable reception .
Why it is a fave : AI agents can make a adult difference when it comes to productiveness — if they are work as intended . make human in the feedback loop helps prevent AI agent from locomote off the rail , but too much human oversight can slack down physical process and diminish the efficiency these AI agent are suppose to bring . HumanLayer seems like a nice happy medium ; it bring in human oversight just when it ’s want and does n’t ask it when it is not .
Raycaster
What it does : inquiry federal agent for enterprise sales .
Why it is a fave : This is the first go-ahead sales run gen software I ’ve had reason to get emotional about ( sorry ) . Raycaster ’s approach is to find very specific details on a likely gross sales objective , like what science lab equipment the company expend or what the company ’s CTO discussed at a recent conference , to pitch them at the right time and in the ripe way . This stands out among a wave of lead gen startups that seem to still be focalize on just aggregating surface - spirit level info .
Join us at TechCrunch Sessions: AI
Exhibit at TechCrunch Sessions: AI
Galini
What it does : Compliance guardrails for AI applications .
Why it is a fave : Galini give enterprises a shaft that have it well-off to fix up AI guardrails based on both company policies and regulations for their AI program program . Plus , putting these controls in the workforce of enterprises gives them more exemption and allow for them to evaluate how effective the safety rail are .
CTGT
What it does : AI tool set that facilitate enterprise customers manage hallucinations .
Why it is a fave : AI hallucination are a big job without an easy fix . While CTGT ca n’t prevent all hallucination , its approach of actively monitor and scrutinise an enterprise ’s models , allowing it to better spot abnormalities and potential delusion , seems like a nice upgrade to the other options out there . The fact that the troupe is already testing its tech with Fortune 10 caller is also a good mansion that potential customer are look for a tool like this .