Latent is an AI engineering firm that designs, builds, and runs production-grade AI agents for enterprises in cybersecurity, defense, fintech, consumer, and enterprise verticals. The company grounds agents in client systems to handle functions like service desk, sales, finance, IT operations, and data analytics, with human escalation only for complex cases. Latent also trains client teams to run and maintain these AI systems in production.
Funding
Funding not disclosed
Founders
Product
Problem
Many enterprises deploy AI tools, copilots, and automations, but these additions rarely integrate AI into core business operations. Production-grade AI agents require systems built for an organization's specific data and operational constraints, and most companies lack the discipline and methodology to make AI work reliably in real-world environments.
Solution
Latent is an AI engineering firm that designs, builds, and runs AI agents for enterprises that cannot afford failure. The company grounds agents in client systems and documentation, enabling them to handle end-to-end workflows across service desk, sales cycle, financial operations, IT operations, and data analytics. Agents surface only the cases that need human intervention, while teams step in to make decisions on the hardest problems. Latent also trains client workforces to run and maintain these AI systems, ensuring the technology remains a living, cultivated part of the business rather than a static installation.
Target Audience
Primary customers are enterprises in cybersecurity, defense, fintech, consumer, and enterprise verticals that need production-grade AI agents integrated into core operations and cannot afford system failure.
Features
- AI agents for service desk, sales, finance, IT operations, and data analytics, grounded in client documentation and systems
- End-to-end automation of workflows, from customer requests to invoice reconciliation and incident triage
- Human escalation only for cases that require judgment, with risk flags and disruption alerts surfaced early
- Plain-language data querying that generates sourced answers and on-demand reports from source data
- Methodology developed from production deployments across enterprise, government, security, health, and finance sectors
- Workforce training programs to enable client teams to run and adapt AI systems in production