AI integration for business applications
Add AI to the software and workflows your business already uses
Morton Technologies integrates AI into existing cloud applications, internal systems, portals, and SaaS products. We connect the model to the right data, permissions, business rules, user experience, and review controls so the result can operate in production.
Where AI can help
Focused capabilities attached to a real workflow
The best integration is rarely a general-purpose chat box. It is a well-defined capability placed where users already need to read, decide, write, search, review, or act.
Document extraction
Read invoices, forms, contracts, reports, correspondence, and attachments; extract structured fields; validate required information; and route exceptions.
Private knowledge search
Answer questions using approved internal material, permission-aware retrieval, citations, document metadata, and feedback from users.
Review and quality checks
Identify missing documentation, conflicting values, unusual patterns, policy concerns, or issues that deserve a person’s attention.
Drafting assistance
Generate responses, summaries, reports, descriptions, and customer communications from known case data and approved guidance.
Workflow automation
Classify requests, recommend the next step, prepare system updates, and execute bounded actions only after the required validation or approval.
AI features for SaaS
Add differentiated, account-aware AI capabilities to an existing software product with usage controls, cost monitoring, and product analytics.
Integration architecture
More than an API call
A production AI feature needs a deliberate boundary around what the model can see, generate, recommend, and change. We design the surrounding software as carefully as the prompt or model selection.
- Identity, tenant isolation, and role-based access
- Data preparation, document ingestion, and retrieval
- Prompt and response management
- Structured outputs and deterministic validation
- Model choice, fallback behavior, and cost controls
- Evaluation datasets and regression testing
- Human approval for sensitive or consequential actions
- Logging, feedback, monitoring, and support workflows
A typical flow
- Understand the request.
Capture user context, permissions, account, workflow state, and the desired task. - Retrieve trusted context.
Query allowed documents, records, services, and business rules. - Generate a bounded result.
Ask for a structured answer, recommendation, draft, or proposed action. - Validate and review.
Check required values, sources, policies, and confidence; involve a person when needed. - Record the outcome.
Store the result, sources, feedback, and approved action for traceability.
A safer path to value
Assess, prove, integrate, and measure
Select
Choose a frequent, costly workflow with accessible data and a measurable definition of better.
Prove
Test representative examples, integration constraints, output quality, latency, and operating cost.
Integrate
Place the capability inside the existing application with security, review, fallback, and support controls.
Improve
Measure accuracy, completion time, exception rate, adoption, cost, and user corrections.
When RAG is appropriate
Ground AI in information your organization controls
Retrieval-augmented generation can help when users need answers synthesized from changing or private material. It is not a universal database replacement. We determine whether semantic retrieval, exact search, structured queries, or a combined approach best fits the question.
A useful knowledge system also needs document ownership, metadata, access controls, source links, freshness rules, evaluation, and a process for correcting weak answers.
Start with one valuable workflow
Where could AI remove the most friction?
Bring a process, sample documents, an existing application, or a product idea. We will help evaluate the data, risks, architecture, and smallest credible path to production value.
Discuss an AI Integration