We Build New Angles Into Systems.

We Build

Into Systems.

Contextual AI infrastructure, multi-agent architecture, and strategic engineering for teams building systems that endure.

Most organizations bolt on AI. Few engineer the architecture beneath it.

Raw model intelligence is now a commodity.
Without cohesive structure, it yields fragmentation and operational noise.

Context evaporates between sessions. Decisions lose systemic continuity.
Teams optimize isolated prompts instead of durable workflows.

The bottleneck is rarely the model.
It is the context architecture and underlying data topology.

Operating Architecture

  1. 01

    Proprietary Products

    We architect first-party intelligence platforms. Mandalora provides the persistent contextual memory layer across AI models. SourceProject, Affilume, and Supersquid deliver autonomous multi-agent orchestration, revenue attribution, and real-time data intelligence at the systemic level.

  2. 02

    Systems Architecture

    For enterprises engineering mission-critical AI workflows, we design the substrate beneath the application: dynamic context routing, multi-agent orchestration, state persistence, and deterministic decision pipelines that remain coherent under scale.

  3. 03

    Strategic System Audits

    We rigorously evaluate AI technical roadmaps, audit vendor architecture, identify critical structural vulnerabilities, and de-risk deployment paths before technical debt compounds into systemic failure.

Tools change weekly. Fundamental system architecture compounds forever.

Initiate System Review → We partner with technical teams where context fidelity and architectural precision are non-negotiable.
Proprietary Infrastructure

Systems Engineered for Scale.

Context Infrastructure · Layer 01

Mandalora

The persistent context fabric that unifies models and tools, preserving architectural memory so organizations think in systems, not ephemeral chats.

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Orchestration Infrastructure · Layer 01

SourceProject

Autonomous project intelligence and multi-agent coordination infrastructure built for technical agencies and studios executing complex workflows.

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Attribution & Revenue Intelligence · Layer 01

Affilume

Advanced multi-touch attribution modeling and partner revenue flow illumination engineered for complex, privacy-first web environments.

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Data Intelligence · Layer 01

Supersquid

High-throughput data extraction and structured enrichment pipelines engineered for teams operating at real-time execution speeds.

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Architectural Paradigms

Engineering Systems Beyond the Prompt.

State & Persistence · Paradigm 01

Eliminating Context Amnesia via Persistent Memory Fabrics

Frontier generative models remain fundamentally stateless computation primitives. When enterprise workflows span multiple models, long durations, and complex toolsets, valuable operational context evaporates between queries. Source78 engineers persistent context memory graphs (Mandalora) that maintain continuous architectural awareness, transforming ephemeral prompts into cumulative organizational intelligence.

Autonomous Orchestration · Paradigm 02

From Passive Issue Trackers to Live Agentic Execution Meshes

Traditional agile boards record historical development after the fact. In high-velocity engineering teams deploying concurrent AI coding agents, passive tracking creates synchronization bottlenecks. Our orchestration substrate (SourceProject) models live codebase dependencies into dynamic dependency topologies, autonomously scheduling tasks, routing PR reviews, and arbitrating worker contention in real time.

Deterministic Attribution · Paradigm 03

Privacy-First Incrementality & Multi-Touch Revenue Graphing

Third-party cookie deprecation and privacy-focused client sandboxing have broken legacy tracking pixels. Operators lose immense margin to misattributed channels and affiliate fraud. Through cryptographic event ledgers and graph attribution modeling (Affilume), we provide mathematical visibility into true touchpoint incrementality across complex multi-channel customer journeys.

Data Pipelines · Paradigm 04

High-Throughput Extraction with Self-Healing DOM Transformers

Dynamic web applications continuously evolve, instantly breaking brittle scraping scripts, while heavy multi-modal LLM extraction introduces prohibitive latency and cloud compute costs. Our extraction engine (Supersquid) pairs lightweight, adaptive DOM healing with streaming micro-extractors, delivering structured, schema-validated data at sub-second speeds.

Direct Inquiries & Architecture Review

Let's engineer systems
that outlast the hype.