When your AI requirements don't fit a product box, we don't force them. We engineer systems designed for your data, your compliance constraints, and your stack — with production deployment and your team fully trained at the end.
Most enterprise AI needs are well-served by our packaged products. Custom engineering is the right choice when your requirements go beyond what packaged tools can handle.
You're extracting structured data from proprietary document types — schemas, terminology, or formats that standard products handle poorly or not at all.
You need AI connected to legacy systems, proprietary APIs, or internal platforms that no standard connector supports.
Regulation mandates on-premises AI processing, a specific cloud region, or an isolated environment that standard deployments can't accommodate.
You need fine-tuned models for a specific vertical — legal, medical, financial, or technical — where general models produce unacceptable error rates on your data.
You're processing at a scale — millions of documents, real-time inference, or sub-second latency — that packaged products aren't architected for.
You're deploying AI across multiple business units, geographies, or customer tenants — each with separate data, access rules, and configurations.
Handle 10× the data volume without scaling your team
End-to-end AI processing pipelines — ingestion, preprocessing, model inference, post-processing, and output delivery — designed for your specific data types, volumes, and latency requirements.
Your knowledge base, searchable with precision at any scale
Custom Retrieval-Augmented Generation implementations with specialized chunking strategies, embedding models, vector stores, and retrieval logic tuned to your corpus and query patterns.
AI that runs inside your existing tech stack, not alongside it
Production-grade AI backend services — REST APIs, event-driven processors, batch jobs — that expose AI capabilities to your applications without coupling them to third-party AI platforms.
Automate workflows your packaged tools can't reach
Custom MCP connectors that give AI models secure, controlled access to your specific systems, tools, and APIs — enabling agentic workflows tailored to your exact business processes.
Domain accuracy that general models can't match on your data
Domain-specific model fine-tuning for industry terminology, proprietary formats, and specialized tasks where general models underperform on your data.
Ship with confidence — measurable quality before go-live
Custom evaluation harnesses for testing AI performance against your specific criteria — accuracy on your document types, compliance with your business rules, and alignment with your quality standards.
From first conversation to production deployment — a predictable process with no ambiguity at any stage.
We map your systems, data sources, compliance constraints, and measurable success criteria before anything is designed.
A technical architecture proposal with delivery milestones, team responsibilities, and a clear definition of done.
Agile sprints with working demos at each checkpoint. You review and redirect before we move forward.
Production deployment with full documentation, runbooks, and your team trained to operate it. All IP, all code — yours.
Five things that distinguish every custom engagement we run.
Every engagement is AI-native engineering. Not a generalist IT consultancy that bolts on AI as an add-on service.
Custom builds connect with or extend our product suite — AI Chat, DocuFlow, and the Management Portal. No orphaned systems.
Success criteria, benchmarks, and acceptance conditions are agreed in writing before we write a line of code.
Our team operates across Latin America, the US, and Europe, delivering projects in English and Spanish. Custom systems we build are designed from day one for multilingual data, multi-region compliance, and organizations whose teams don't all work in the same language.
Deploy AI Chat for the user-facing conversational interface, then use Custom Engineering to build the proprietary connectors that link it to your specific systems.
The result: an AI Chat experience that actually knows your CRM, ERP, or proprietary platform — not just your document library.
Use Custom Engineering to build the extraction pipeline for your proprietary document types, then surface the results through the Management Portal for team review and approval.
The result: structured output from any document format your organization uses, reviewed through the same familiar interface.
For fully bespoke AI systems, Custom Engineering builds the core, and Managed AI Operations monitors and maintains it in production — so your team never has to maintain the AI directly.
The result: a bespoke AI system in production with ongoing monitoring — without permanently adding AI engineers to your payroll.
We'll scope it, define measurable success criteria, and show you what the system looks like before we start. No ambiguity about what you're getting — or when.
Teams use InterConnecta AI to connect knowledge, automate complex workflows, and launch AI-powered experiences — with less risk and faster operational payoff.
