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.
Model
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 — not just demo.
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