Applied AI & R&D
We move past the chatbot era into systems that plan, use tools, and act. The model is the commodity. Reliability comes from the harness engineered around it: tools, context, verification, and guardrails.
Focus areas
Each lane feeds the others. Perception work sharpens the sUAS product, and edge constraints shape how we build agents.
Systems that plan, use tools, and act, with a human in the loop.
Tool-using agents for bounded, multi-step mission tasks
Retrieval and knowledge assistants over manuals, policies, and ops data
Approval gates and escalation for actions that can't run unattended
Inference at the tactical edge: denied, disconnected, low-SWaP.
Distilled and quantized models sized for embedded and edge hardware
Offline-capable inference for disconnected and contested environments
Private and open-weight deployment when data can't leave the boundary
Perception and autonomy across real-world sensors.
Multi-modal sensor fusion for detection, localization, and classification
Perception models tuned for noisy, real-world signal conditions
Forecasting and anomaly detection for decision support and readiness
Harness engineering
A capable model is now a commodity you can swap out. What makes an agent reliable in the field is everything engineered around it — tool orchestration, context management, verification, and guardrails. That control layer is what we build, evaluate, and govern.
Approval gates, role-aware access, and human review for workflows that can't run fully unattended.
Visibility into prompts, tool calls, and agent decisions so teams can inspect and improve every run.
Task-specific evals that measure quality, reliability, and regressions before broader rollout.
Ongoing monitoring for drift, failure patterns, and workflow health after deployment.
For sensitive missions we design for self-hosted and open-weight deployment, so data and models stay inside the boundary, and the R&D feeds directly back into the sUAS product.
Program engagement
We build the governance, evals, and observability that make these systems safe to field.
Best fit
Teams that need a focused software partner for product, integration, or operational-delivery work.
Discussion topics
Product fit, teaming structure, integration scope, field constraints, and execution model.
Contact
sales@ancile.io