Repository / Systems

Active Research Systems

Deep Bound Research develops systems across two layers: reusable research infrastructure and flagship platforms. Reusable infrastructure includes engines, protocols, SDKs, routing systems, and context tools. Flagship systems live under House-Labs and include Ex1, Boundary, Plateau, StrongHold, and Cerberus.

CONTEXTMEMORYRUNTIMEPOLICYEVIDENCERETRIEVALSIMULATIONGOVERNANCECONTEXT ↗↖ RUNTIMEPOLICY ↘↙ GOVERNANCE
Core System
Private Beta Preparation

Ex1

AI Workspace / Operator Runtime

An AI-native workspace for governed agent execution, multi-surface work, operator-controlled automation, and recoverable human-AI workflows.

Why it matters

A desktop-first operator runtime that gives teams a single surface to plan, run, and recover AI work across agents, tools, and context.

Architecture Development

StrongHold

Data Ingest & Archive Platform

A governed data ingest and archive platform for deduplicating, compressing, versioning, retrieving, and restoring large research and AI-system data streams.

Why it matters

Data ingest · Deduplicated archives · Adaptive compression · Retrieval · Restore planning.

Runtime Engine
Research Prototype

Boundary

Simulation Infrastructure

A simulation and environment framework for testing AI behavior, system interaction, workflow reliability, and controlled runtime scenarios.

Why it matters

Provides high-fidelity, repeatable environments for evaluating agents against safety and performance benchmarks before production exposure.

Internal R&D

Cerberus

Defensive Security Harness

A defensive security research system for sandboxed analysis, runtime mitigation planning, blast-radius reasoning, and evidence-led security workflows.

Why it matters

Provides a constrained, evidence-led layer for studying agent failures and runtime risks without enabling offensive use.

Research Studio
Concept + Prototype Planning

Plateau

Design-Space Exploration Studio

A systems-design and concept-board workspace for exploring advanced products, hardware concepts, operational architectures, and frontier infrastructure ideas.

Why it matters

Gives the lab a structured surface for generating, ranking, and documenting candidate architectures before commitments are made.

Open Source
Open Source Preparation

ACE

Context Engine

A context and retrieval engine for ranking, routing, and surfacing relevant information across complex AI workspaces and agent workflows.

Why it matters

Treats context as infrastructure: ranks, prunes, and routes sources so agents see only what is strictly necessary for the current step.

Research Structure

Deep Bound Research uses a staged R&D structure: early projects begin in a private founder workspace, reusable research infrastructure moves into Deep-Bound-Research, and flagship systems live under House-Labs.