Build agentic AI in the browser— without losing control.

I design browser-native, edge, and enterprise agentic systems—from MiniLM semantic retrieval in the browser to WebAssembly containment, explicit capabilities, verified evidence, deterministic state, bounded tools, and replayable decisions. Contact me to evaluate an AI product, reduce its authority and data-exposure surface, or apply the OverLift Method where trust matters.

01
Build browser-native and edge AI

Use WebAssembly, Workers, local retrieval, and MiniLM embeddings for private, low-latency intelligence close to the user.

02
Turn agent ideas into security-bounded systems

Contain risky execution, expose only typed capabilities, and define identity, policy, approvals, recovery, and proof before an agent acts.

03
Apply the OverLift Method

Connect the question to evidence, compare allowed paths, act, and keep a receipt that explains why.

Browser agentic AI Edge AI / MiniLM OverLift Method Wasm sandboxing Capability security Deterministic systems Semantic Bridge .NET / Azure
SECURE AGENTIC PRODUCT WORK

Start with what the agent must never be able to do.

A productive architecture conversation should define the data boundary, untrusted execution surface, allowed capabilities, approval rules, exact state owner, failure behavior, recovery path, and evidence needed to prove all of it.

Explore the security architecture See the complete Method
PRIVACY What information leaves the chosen boundary?

Prefer browser-local, same-origin, or offline processing; disclose only the approved evidence a remote service actually needs.

SECURITY What can this code or agent reach, call, change, or persist?

Use worker and WebAssembly containment, explicit imports, typed tools, deadlines, allowlists, and fail-closed defaults.

AUTHORITY What is allowed to become official truth or state?

Keep identity, permissions, policy, approval, exact execution, verification, receipts, and replay outside probabilistic control.