Computers turned into a
Digital Human.

EmulatedHumanoid  /  Digital Human  /  Windows Native

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The Problem
Every AI agent that
sees your screen
is too slow.

Screenshot-based agents send images to the cloud, taking 4 seconds per click. They hallucinate, blow up context windows, and break when a UI button moves 10 pixels. That's a tech demo, not an enterprise product.

Our Approach
We read the OS.
At the kernel level.

We bypassed the cloud. Using native Windows C++ UIAutomation hooks, our Semantic Sniper pierces the DOM in 1 millisecond. Combined with local semantic embeddings and procedural memory, we deliver deterministic, zero-latency automation.

02 — Architecture

Three core layers. Zero hallucination.

01
Semantic Sniper
C++ · ControlFromPoint

We don't parse the whole screen. When the agent acts, a background thread instantly queries the OS for the exact accessibility element at that pixel. Deep nested web DOMs pierced in sub-milliseconds.

01
02
Procedural Memory
Flash-Freeze Compiler

Stop paying LLMs to guess where the "Send" button is. Record a workflow once, and our compiler saves the semantic UI targets as a JSON skill graph for instant, deterministic replay at machine speed.

02
03
Self-Healing UI
pplx-embed · INT8

Hardcoded string matching is brittle. We use lightweight, local quantized embedding models to match the semantic intent of UI elements. If "Chat" changes to "Messages", the agent self-heals anyway.

03
03 — The Conductor

One Orchestrator. A Swarm of Specialists.

We ripped the "Brain" out from the "Hands." A heavy reasoning model plans the objective and routes atomic tasks to fast, specialized sub-agents. No more monolithic models exhausting their context windows.

01
GUI Driver
Powered by sub-second flash models. Blindly and rapidly executes UI clicks based on strict semantic targets provided by the Conductor.
02
Terminal Driver
Bypasses the GUI entirely. Executes native PowerShell commands to manipulate files instantly when clicking is too slow.
03
Anti-Hallucination Shield
Middleware that intercepts invalid tool calls and physically forces schema corrections into the prompt, preventing LLM death loops.
04
RAG Memory Agent
Uses local vector search to retrieve pre-compiled JSON skills matching the Conductor's current sub-goal.
The Conductor
Orchestrator
Live Task Trace
→ waiting for task
0ms
DOM Sniper Latency
0px
Magnetic Snap Radius
10
Hallucination Loops
0%
Deterministic Replay
05 — Feature breakdown
01 / Perception
Semantic
Sniper
Using Windows ControlFromPoint, we pierce through 20 layers of nested web DOMs the exact millisecond a click happens. No waiting for background state updates.
auto.ControlFromPoint(x, y)
if not target:
  snap_to_nearest(60px)
OS Layer
Sub-1ms
02 / Resilience
Magnetic
Snapping
Humans click the empty padding inside buttons, not the text. Our Euclidean distance algorithm mathematically snaps lazy clicks to the nearest semantic bounding box.
dist = math.hypot(cx-x, cy-y)
if dist < 60:
  target = closest_el.Name
Math Layer
Active
03 / Orchestration
Multi-Model
Harness
The Conductor manages global context and routes tasks to the CLI Agent or the GUI Agent. Sub-Agents only see their local context, saving massive token costs.
plan = Conductor.think(goal)
for task in plan:
  ui_driver.run(task)
Routing
Orchestrating
04 / Robustness
Anti-Hallucination
Shield
Small models stubbornly repeat bad tool calls. Our middleware intercepts invalid JSON actions and physically forces the correct schema into the error prompt to guarantee recovery.
if act not in tools:
  return "CRITICAL ERROR: Use exactly {'action': 'click'}"
Middleware
Shielded
05 / Memory
Flash-Freeze
Compiler
Replaces stateless guessing with procedural memory. Records deterministic JSON workflows natively, bypassing the cloud, and executes them at machine-speed.
{
 "action": "click",
 "semantic_target": "Send"
}
Memory
Compiled
06 — Under the Hood

Drives the machine. Like a human.

Watch the Multi-Model Harness in action. The Conductor decides what to do, the Terminal Driver finds the files natively, and the GUI Driver executes the clicks. All protected by semantic embeddings.

› eh run "Email Q3 report to Boss"
✓ Conductor routing to Terminal Driver...
✓ [Terminal] File found: C:/docs/Q3.pdf 4ms
✓ Conductor routing to GUI Driver...
› GUI.click(semantic_target="Compose")
✓ Magnetic snap successful (dist: 12px)
› GUI.click(semantic_target="Send")
⚠ UI changed: 'Send' not found. Running pplx-embed...
✓ Semantic match found: 'Submit' (similarity 0.94)
✓ Task complete. (Total tokens saved: 45,200)
›

Your machine. Your rules.

Stop relying on fragile cloud-vision tech demos. Deploy autonomous, deterministic, multi-agent swarms to conquer legacy Windows workflows.

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