We integrate AI with .NET applications, ERP and CRM systems such as Dynamics 365 and SAP, SharePoint and Microsoft 365, SQL and PostgreSQL databases, and custom line-of-business software. If a system has an API, we connect to it directly. If it doesn’t, we build an integration layer around it.
AI integration for enterprise apps
We connect AI to the core systems of your business.
Blackthorn Vision specializes in bridging AI and .NET applications, ERP, CRM, legacy databases, and cloud infrastructure. You get modern, sophisticated AI features and tools that work inside the daily workflows where your people already do their jobs.
Microsoft Partner / ISO 27001 / 15+ years in .NET / Since 2009
Enterprise AI integration solutions
Most enterprise AI projects take similar directions when it comes to model choice. But it doesn’t mean that there is a universal path for most of them – not for our AI team.
We make sure the model can read data from your ERP, write back to a CRM, and pass any security review. Our enterprise AI integration services cover every aspect, including the connectors, data pipelines, access rules, and monitoring that turn AI into a working part of your existing applications.
Blackthorn Vision has built on .NET since 2009, and one of our strongest areas of expertise is modernizing legacy systems. AI integration is a part of this process. We know that many core business processes still depend on dated services and interfaces, and we design enterprise AI integration solutions that work with them.
Why enterprise AI projects get stuck
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AI is not a part of your core systems
The AI may be up and running, but it is not connected to the ERP or CRM where employees work every day. Instead, they have to open a separate tool and transfer information between systems. Nobody likes extra steps, and that one quickly becomes a hassle. Employees eventually return to the tools they are used to.
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Data spread across different systems
Customer data is stored in the CRM, orders in the ERP, contracts in SharePoint, and numerous nuanced documents and guides lie in mailboxes. These systems don’t always update at the same time. If AI can access only some of the data, or works with an old copy, it may give incomplete or outdated answers and mislead users. People won’t trust it.
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Legacy .NET systems make AI hard to adopt
Many critical business processes still run on older .NET Framework or COM-based applications that do not have modern REST APIs. Connecting AI to these systems can be very difficult. Many modernization teams suggest replacing them altogether. Eventually, what was supposed to be an AI project turns into a costly, multi-year system overhaul.
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Security and compliance delay the launch
Even if your AI works in testing, IT and legal teams may stop the production rollout if they find out security and compliance requirements weren’t considered from the start. Data residency, access controls, and nuanced audit requirements can force the team to redesign parts of the system. This moves the launch date ahead.
Our enterprise AI integration services
AI integration solutions for enterprise
Our enterprise AI integration services connect LLMs, RAG pipelines, and AI agents to your existing .NET, ERP, and cloud systems. As a Microsoft Partner with more than 15 years of .NET work, we build AI integration services for enterprise environments where uptime, access control, and old code all have to be taken into account.
LLM and RAG integration into enterprise apps
We connect GPT, Claude, and other large language models to your .NET backends, SharePoint, Dynamics 365, and custom enterprise systems. RAG pipelines ground each answer in your own documents and records. Source-system access rules carry over, so users get answers built only from data they are allowed to see.
AI agent integration into enterprise workflows
We build AI agents that work inside your ERP, CRM, and workflow tools through .NET services and Azure connectors. Each agent works with a defined set of permissions and logs every action. Your team can see what it did and why. For standalone agent projects, see our AI agent development service.
Legacy system AI modernization
We add AI capabilities to .NET Framework and COM-based applications without rewriting them. A thin integration layer, such as a modern API in front of the old service, lets AI read and write data while the original system keeps running. For broader upgrades, see our application modernization services.
AI data pipeline and infrastructure
AI integration solutions for enterprise systems depend on a reliable data flow. We build ETL and ELT pipelines, vector stores, and data connectors that keep AI in sync with your source systems. We also monitor these pipelines, so stale or missing data gets caught before it affects answers.
Why enterprises choose Blackthorn Vision for enterprise AI integration services
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15+ years of .NET integration experience
Companies looking for the best enterprise AI integration services often already have a model proven in testing. What they are looking for is a team that can connect it to their systems safely and keep it running and scalable over time.
We know .NET internals, COM interop, WCF, and the enterprise patterns that core business systems were built on years ago. Many AI teams have never worked with them. This experience lets us connect AI to the systems your business relies on without risking stability or disrupting daily processes.
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Microsoft Partner with Azure-native integrations
Blackthorn Vision is a Microsoft-partnered .NET and AI development company that helps enterprise teams build and modernize complex software products. We integrate with Dynamics 365, Azure AI Search, Microsoft Graph, and SharePoint through their supported APIs and connectors to avoid fragile custom workarounds.
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Security designed into the architecture
Data residency, role-based access, and audit trails are part of the integration; they are agreed upon during the first architecture session. We operate under an ISO 27001-certified information security management system and ensure our IT and security teams regularly review the design and catch issues well before production.
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Integrations ready for production
We deliver integrations with monitoring, error handling, retry logic, and failover, tested under realistic – not optimistic – load. Top enterprise AI integration solutions are those that keep working in daily use long after the sandbox demo. That is the standard we build to.
Technologies we use for enterprise AI integration
All technologiesWe choose tools based on the systems you already run and the security rules they follow. Identity, security, and monitoring tools are necessary; no IT team will approve an integration they can’t control or observe.
AI and LLM
Azure OpenAI, Semantic Kernel, Microsoft Agent Framework, LangChain, RAG pipelines, ML.NET
Enterprise connectors
Microsoft Graph API, Dynamics 365 API, SharePoint, Azure Service Bus, SAP connectors
How Blackthorn Vision integrates AI into your enterprise systems
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01
Five steps of enterprise AI integration services
Our enterprise AI integration services usually follow five steps, and each one ends with a document or a working result you can review. This is done to deliver AI integration services for enterprise teams whose in-house IT departments need to approve each stage before moving to the next one.
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02
System and data mapping
We start by listing the systems involved, their APIs, and how data moves between them. We also map security boundaries and compliance requirements, such as where it’s allowed to store and process data. You receive an integration architecture map showing how the systems connect and where the risks lie.
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Integration architecture design
Based on the map, we design the connectors, data pipelines, and security model. The design also covers error handling and the sequence of actions for cases when one of the connected systems is unavailable. You get a technical architecture document that your IT team can review before development.
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04
Connector development and testing
We build the .NET connectors, API wrappers, and data pipelines, then test them in a staging environment with realistic data. This stage often reveals problems in legacy systems, so we fix them before they reach users. At the end of this step, you have a tested integration layer running in staging.
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05
Security and compliance review
Before production, we validate access controls, check data residency, and confirm that audit logging captures what your compliance team needs. Your IT team reviews the results and signs off. You receive a security review report for your records.
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06
Production deployment and monitoring
We roll out bit by bit, starting with a limited group of users, and set up monitoring and alerts. Once the integration is stable, we hand over an operations runbook that explains how to monitor it, respond to incidents, and update it. You get a live AI integration and the documentation your team needs to run it.
FAQ
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What enterprise systems can you integrate AI with?
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Can you integrate AI with our legacy .NET or COM-based applications?
Absolutely. We work with .NET Framework applications, WCF services, and COM components. The usual approach is to put a modern API in front of the legacy system, so AI services can call it without touching its core logic. For WCF services, CoreWCF can bring existing contracts onto modern .NET when that makes sense for the project.
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How do you handle security and data residency requirements during AI integration?
We design for them from the first architecture session. AI services run in the Azure regions your policies allow, and data access follows the permissions of the source systems, so users only see answers built from data they’re allowed to view. AI requests and actions are logged for audit. Our work runs under an ISO 27001-certified information security management system.
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Do we need to replace our existing systems to integrate AI?
In 95% of cases, no. Our enterprise AI integration solutions are designed to work with the systems you have. We add connectors, APIs, and data pipelines around them, so your core applications keep running as before.
If part of a system does need modernization, we’ll tell you where and why, and you decide whether to do it.
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How do you ensure our proprietary company data and customer privacy remain secure?
Client data stays in the client’s environment. We work in private Azure deployments, send nothing to public model endpoints, and set role-based access in the first week.
As an artificial intelligence consulting company working under HIPAA and GDPR, we sign BAAs and NDAs and pass client security audits several times a year. Your compliance team can join project calls from day one.
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How long does an enterprise AI integration project take?
It depends on the number of systems, the state of their APIs, and your internal security review process. A project with one or two systems that already have modern APIs moves faster than one involving legacy applications across several business units.
After the system and data mapping step, you get an integration timeline. We deliver enterprise AI integration solutions in phases, so the first connected system can start working before the rest are finished.
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Do you provide ongoing support after the integration is deployed??
Yes, we provide long-term AI integration services for enterprise clients and agree on the support part during the release stage or earlier.
For most of our clients, we stay on to monitor the integration after launch, handle incidents, and update connectors when systems change or when they collect user feedback and want to make improvements. Model providers also regularly retire older model versions, so someone has to test the integration against newer ones and switch it over.
