Reachlatent
Latent (now operating as Archer) is an AI engineering firm that designs, builds, and runs production-grade AI agents for enterprises in high-stakes industries. The company deploys agents within the client's own cloud environment, using a license-based model tied to agent performance rather than token consumption. Its agents handle end-to-end workflows across service desk, sales, finance, IT operations, and data analytics, with human escalation reserved for cases requiring judgment.
- Artificial Intelligence
- AI Agents
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
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. The company operates within the client's own cloud environment, keeping data and AI systems under the client's security, privacy, and compliance requirements. A license-based model provides cost clarity, aligning success with agent performance rather than token consumption.
Target Audience
Primary customers are enterprises in cybersecurity, defense, fintech, consumer, healthcare, marketplace, 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
- Deployment within the client's own cloud environment, preserving security, privacy, and compliance requirements
- License-based pricing model tied to agent performance, not token consumption
- Continuous feedback, evaluation, and monitoring to improve agent accuracy and effectiveness over time
- Hands-on workshops for engineering, data, and business teams to establish working methods before deployment
- 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