Kelet Inc.
Kelet helps AI and LLM production teams automatically discover why their agents fail and provides ready-to-ship fixes.
At a Glance
- AI Engineering Teams
- LLM Application Developers
- Enterprise AI Teams
- Startups building AI agents
AI Tools by Kelet Inc.
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Kelet
AI Agent Reliability Platform
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Latest News
Kelet (kelet.ai) — continuously diagnoses why your LLM apps and AI agents fail in production.
Kelet: The New AI Detective for Debugging and Fixing Production Agent Failures.
Almog Baku featured speaker at AI Dev TLV 2025 regarding 'Feedback Is All You Need'.
Products & Services
A platform that continuously diagnoses why AI agents fail in production, provides evidence-backed root-cause analysis, and generates prompt patches.
Market Position
Kelet distinguishes itself from standard observability tools by moving beyond reporting to active diagnosis and automated remediation (fixing) of agent failures.
Leadership
Founders
Almog Baku
3x founder (1 exit). Previously Innovation Tech Lead at Rivery (acquired by Boomi), Co-founder & CEO at Natun.ai, and Co-founder & CTO at Rimoto (acquired). Founder of the GenAI Israel community and creator of the open-source Raptor.ml infrastructure.
Executive Team
Almog Baku
Founder & CEO
LLM engineering expert and seasoned entrepreneur. Previously held leadership roles at Rivery (acquired by Boomi) and founded multiple startups including Natun.ai and Rimoto.
Founding Story
Founded by a team of ex-Kubernetes maintainers and infrastructure veterans to eliminate the guesswork in debugging production AI agents and ensure reliability at scale.
Business Model
Revenue Model
Usage-based subscription model based on the number of sessions analyzed.
Pricing Tiers
500 sessions/month, 15-day retention
5,000 sessions included, 30-day retention
Unlimited sessions, custom retention, SSO/SAML, SLA
Target Markets
- AI Engineering Teams
- LLM Application Developers
- Enterprise AI Teams
- Startups building AI agents
- Debugging production LLM application failures
- Continuous reliability monitoring for AI agents
- Analyzing complex multi-agent architectures
- Identifying and fixing edge-case failure patterns
- Used by a pilot cohort of world-class AI engineering teams