Contextual AI Launches Agent Composer--AI for When It Actually Is Rocket Science
New platform powers AI agents for aerospace, semiconductors, manufacturing, and other advanced industries, cutting complex tasks from hours to minutes
MOUNTAIN VIEW, Calif., Jan. 27, 2026 /PRNewswire/ -- Contextual AI, the enterprise AI company building the unified context layer for engineering disciplines, today announced the launch of Agent Composer, new capabilities for building AI agents that can automate complex engineering work, even when it actually is rocket science.
Engineering teams across semiconductors, manufacturing, and other technical industries spend much of their time on routine, but knowledge-intensive tasks: device log analysis, production planning, customer engineering ticket resolution, etc. While critical, these tasks consume valuable engineering time and limit the solution space in which subject matter experts can explore new possibilities.
"We've worked with customers across advanced industries, and they often struggle to build AI that works for their technical tasks," said Douwe Kiela, CEO of Contextual AI. "The problem was never the models. It was giving models access to the context buried in technical documentation, logs, and specifications. We're helping companies do this in the right way to accelerate real-world engineering work."
Agent Composer is the infrastructure and orchestration layer that manages context, enforces guardrails, and maintains agent reliability throughout multi-step engineering workflows—Contextual AI's agent harness—giving AI access to the documentation and institutional knowledge it needs to reliably complete technical tasks.
The platform offers three ways to create agents:
- Start with a pre-built agent: Pre-configured for common technical workflows (e.g. root cause analysis, specification review, compliance checking) and ready to customize for specific requirements
- Generate from a description: Use natural language to describe the workflow, and Agent Composer automatically generates a working agent architecture in seconds
- Build from a blank canvas: Full control for teams that need custom logic, specialized integrations, or novel workflows
Agent Composer also adds a level of control over agent behavior that other platforms can't match. Teams can combine strict rules for high-stakes steps (compliance checks, data validation, approval gates) with dynamic reasoning for exploratory analysis. The result: AI that enterprises can actually trust with complex work.
Early customers are already seeing significant efficiency gains in some of their most critical work.
- An advanced manufacturer reduced root-cause analysis from 8 hours to 20 minutes by automating sensor data parsing and log correlation.
- A global strategy consulting firm reduced manual research from hours to seconds, giving consultants access to relevant case work, answers to complex questions, and prior examples.
- A tech-enabled 3PL provider achieved 60x faster issue resolution by providing instant answers across their entire internal knowledge base.
- A specialty chemicals manufacturer reduced product research from hours to minutes with agents that search patents and regulatory databases.
- A test equipment maker generates test code in minutes instead of days by translating procedures into control logic.
Keith Schaub, VP of Technology and Strategy at Advantest said: "Contextual AI has been an important part of our AI transformation efforts. The technology has been rolled out to multiple teams across Advantest and select end customers, saving meaningful time across tasks ranging from test code generation to customer engineering workflows. This launch adds new capabilities that we expect will unlock additional high-value use cases and further support Advantest employees with a trusted AI companion for complex work."
Agent Composer is available now on the Contextual AI Platform. https://contextual.ai/
About Contextual AI
Contextual AI provides the context layer that makes AI work for expert-level technical tasks. The platform turns hours of complex expert work—technical customer support, device log analysis, patent research, production planning—into minutes. Founded by the team that pioneered RAG at Meta, customers include Qualcomm, Advantest, ShipBob, and NVIDIA.
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