One shared platform
Fragmented computing resources and business systems became a unified, manageable and scalable environment.
Infrastructure for applied AI
ChopInsight builds an AI-ready research platform
Aiursoft brought ChopInsight’s existing infrastructure, emerging AI requirements and business applications into one stable, scalable platform—protecting earlier investments while preparing the business for continued AI adoption.
The organisation
About ChopInsight
Shanghai ChopInsight Intelligent Technology Co., Ltd. specialises in real estate finance and alternative investments. It provides integrated primary- and secondary-market research services for participants across REITs, private real estate funds, Pre-REITs, holding-type ABS, public REIT issuance and asset management, insurance and insurance asset management.
Its competitive advantage comes from a deep understanding of the business models behind underlying assets, combined with expertise in fundamental research, data science, quantitative finance and large language models. Rather than simply delivering information, ChopInsight is building a new research framework around long-term value, deeper insight and a durable technology advantage.
Highlights
Investment protected
Existing equipment was reused while cost-effective resources were selected and adapted for emerging AI workloads.
Operations standardised
Identity, application delivery and operational visibility no longer depend on disconnected manual processes.
AI access governed
Applications can use local and compatible external model resources through a consistent enterprise capability.
01
The challenge
Moving into an AI-enabled future, one server at a time
As ChopInsight expanded, it introduced knowledge bases, data analytics, AI-assisted question answering, research tools, collaboration services and a growing number of business applications. Each system addressed a real need, but the infrastructure beneath them had not evolved at the same pace.
Several traditional rack servers operated alongside public cloud and externally hosted resources. Acquired at different times, from different sources and for different purposes, they had never been designed or managed as a single environment.
Applications were typically deployed and maintained by their respective software suppliers. That approach worked while the estate was small, but became difficult to sustain as applications accumulated different runtime environments, deployment methods and operational practices. Accounts and permissions were managed separately, dependencies were difficult to understand, and operational information was scattered across multiple systems.
This fragmentation affected day-to-day work. Diagnosing a problem depended heavily on individual experience. Upgrades and migrations often required the original supplier. Some environments became harder to maintain over time, and expanding capacity could mean purchasing more equipment and repeating the same deployment work. When external operations staff changed, valuable knowledge could leave with them.
AI introduced a second, closely related challenge. Suitable computing resources could be expensive and complex to specify. ChopInsight needed to avoid hardware that might later prove unsuitable for its software or operational requirements, while simply replacing equipment would have ignored the value of its existing servers.
A software-only delivery would not solve the problem either. Even a well-designed platform cannot provide the expected performance or reliability when its underlying hardware is unsuitable or poorly integrated. ChopInsight needed a coordinated approach that could preserve existing investments, add computing capacity where necessary, and support conventional applications and AI workloads through a common management model.
02
The solution
Hardware and software designed as one system
Aiursoft assessed ChopInsight’s physical equipment, computing resources, application requirements and future AI plans together. Performance, stability, cost and future expansion informed a single design, making hardware selection and adaptation part of the service rather than a separate procurement exercise.
Inputs
Existing servers
New AI compute
Cloud resources
New AI compute
Cloud resources
Shared foundation
Aiursoft managed platform
Capabilities
Identity · AI access
Delivery · Operations
Delivery · Operations
A consistent infrastructure foundation
Previously, one server would often be associated with one application. Under the new model, servers became computing resources within a shared platform while applications were managed independently of individual machines. Existing capacity could be reused more effectively, workloads could share resources with appropriate separation, and validated new hardware could join the same management model.
This separation gave ChopInsight a more flexible foundation. New services no longer had to begin with a standalone environment. Runtime status and upgrades could be managed centrally, and replacing one machine no longer had to become an application-specific infrastructure project.
Unified identity and access
Aiursoft introduced a unified identity layer and connected relevant internal services to it. Users, organisational relationships and access policies could be managed through a common framework, reducing duplicate accounts while establishing a foundation for consistent access governance, service auditing and secure use of internal applications.
AI as a governed enterprise capability
With suitably adapted local computing resources in place, Aiursoft established a unified entry point for AI services. Users and applications could access model capabilities through consistent rules, while permissions, credentials, usage and service health could be managed centrally.
ChopInsight can now balance performance, availability and cost without forcing every application to implement those decisions independently. The technology underneath can change without requiring every consuming application to be redesigned.
Research collaboration on the same foundation
Internal files, research materials, project documents and team collaboration were aligned with the same identity and permission model. For a research organisation with a growing body of specialist material, this simplified everyday collaboration and created a more reliable base for knowledge reuse and AI-assisted research.
Repeatable delivery and operational visibility
Source code, version management and delivery workflows moved into a common platform. Development, validation, release and rollback now follow a repeatable process, while configuration and change history are retained. Developers and AI agents can contribute without making production delivery depend on a sequence known only to one person.
Essential service status and operational records can also be viewed from a common perspective. Teams can investigate across services, understand critical system use, retain records for long-term auditing and build toward future alerting and operational analysis—without exposing the customer’s detailed internal architecture.
03
The results
A capability the company can increasingly control for itself
The project was more than a server migration. It changed how ChopInsight builds, operates and expands its business systems.
Infrastructure became a platform
New services can use shared deployment, management and operational practices rather than introducing another environment and maintenance owner.
Earlier investment keeps working
Resource planning, hardware adaptation and software delivery now form one solution, balancing AI performance with stability and cost.
Knowledge stays with the organisation
Code, configuration and release processes are standardised and versioned instead of living in temporary commands or individual experience.
Identity and AI are shared capabilities
Applications can use a unified access model and governed model resources without repeating account administration or AI integration work.
Operations are easier to understand. Service status and essential records are managed from a unified perspective, supporting faster diagnosis, security auditing and future analysis. Rather than contacting several suppliers to identify where a problem belongs, ChopInsight has a clearer view of the environment it operates.
Most importantly, technology is less likely to limit the speed of the business. Testing, building and release can proceed through a standardised delivery model, while AI agents can assist with code changes and problem analysis inside an established governance framework.
ChopInsight now has a technology platform that can grow with its research business.
Unified. Stable. Scalable. Governable.Build what comes next