Supports hardware, networking, monitoring, backups, operations, and specialized implementation when projects require additional delivery capacity.
Hardware & NetworkMonitoring & AlertsBackup & RecoveryOngoing Ops
AI Efficiency Architecture, Cloud Infrastructure, and Transformation
Reallier / INTJSYS works on high-complexity AI delivery: agent efficiency architecture, cloud-exit / private-cloud infrastructure, and intelligent transformation strategy. We start from real systems, business goals, and organizational constraints, then turn architecture judgment into operable, reviewable, governable capability.
[ FOUNDER ]
Founder
Former SDK Performance Architect at a leading crypto firm (10-person team). Senior Test Developer at Sea Group (Garena). Automation Engineer at Lenovo. Long-running work across high concurrency, microservices, cloud computing, AI engineering stacks, and complex system delivery. Now leads Reallier's three business lines: agent efficiency architecture, cloud-exit / private-cloud infrastructure, and intelligent transformation strategy.
Agent Memory · Harness · Multi-agent
Cloud Exit · Private Cloud · Local Compute
Concurrency · Microservices · Cloud Native
AI-native Workflows · Skill Library
CLOUD EXIT94% Cost Cut300-person headhunting firm: ¥140k/yr → ¥8k/yr. 2-week delivery.
AI INFRA72% Cost CutEducation system: image recognition, queues, and object storage moved off cloud; ¥1.6M saved over 3 years.
AGENT ARCHMemory / Collaboration / HarnessSeparated memory, multi-agent collaboration, and runtime harness for long-running agent systems.
TECH STACKPython · Go · Docker · K8s · Proxmox · ZFS · Tailscale · PostgreSQL · Elasticsearch · vLLM · RAGFlow
[ DELIVERY CAPACITY ]
Delivery Partners
For projects involving hardware, networking, monitoring, backups, ongoing operations, or specialized implementation, Reallier works with long-term engineering partners.
Architecture decisions, delivery standards, and project ownership stay unified. The partnership expands implementation capacity and ongoing support without changing Reallier's responsibility for delivery outcomes.
[ HOW WE WORK ]
How We Work
Start from reality, identify the right business line, then split delivery into phases, metrics, and governance boundaries.
Assess
Business-line Assessment
Review agent prototypes, cloud bills, architecture, workflows, and organizational goals to identify the right line of work.
Phase
Phased Delivery
Deliver executable assets such as memory / harness, cloud-exit / private-cloud plans, AI-native workflows, skill libraries, or agent workspaces.
Govern
Ongoing Governance
Use monitoring, evaluation, reviews, inspections, permissions, and operations boundaries so delivered systems stay traceable and evolvable.
···
[ ENGINEERING PHILOSOPHY ]
Engineering Philosophy
IData Sovereignty
Data Sovereignty
Environment awareness over data hosting.
Reject black-box cloud services. Adhere to Private-First deployment paradigm, ensuring AI logic flow is fully controlled within the client's VPC and security audit system. Delivery equals physical isolation, reducing privacy risk to the engineering theoretical minimum.
IIAtomic Architecture
Atomic Architecture
Low-intrusion, low-entropy architectural principles.
Eliminate logic redundancy of heavy workflow frameworks. Use atomic microservices to encapsulate AI capabilities, enabling seamless integration with existing systems (CRM/OA/ERP) with minimal disruption. No architectural overreach.
IIIDeterministic Observability
Deterministic Observability
Pipeline observability is the lifeline of productivity.
Introduce distributed tracing (Deep Trace) standards. Through strongly-typed protocol constraints, achieve full transparency of model decision paths. End randomness guessing, enable second-level root cause tracing.
IVAction-Oriented Interface
Action-Oriented Interface
Efficiency tools should shift from "conversation" to "action".
Use LLM to extract structured parameters, directly driving underlying engineering scripts or API actions, achieving "intent-is-execution" minimal interaction. Reject efficiency loss.
VSchema-First Protocol
Schema-First Protocol
Completely end the "lossy compression" of unstructured information.
Enforce Schema-based inter-model communication. Prohibit Agents from using natural language to report work — all collaboration instructions must be passed via standard JSON protocols, isolating hallucination risk, exchanging only deterministic data states.
VIProduction-Grade Throughput
Production-Grade Throughput
Ultimate execution efficiency over anthropomorphic logic stacking.
Following enterprise SDK architectural paradigms, deeply optimizing inference paths. In high-concurrency production environments, ensure AI modules have millisecond-level response capability with minimal resource entropy increase. Reject non-production-grade prototypes.
Contact Reallier
If you were referred here, share your cloud bill, current architecture, and main pain point. We will first decide whether a technical assessment is worthwhile.
···