What we build for commercial clients
Each solution below is a complete application rather than a model on its own: the interface your team or your customers use, the integrations into your existing systems, the monitoring, and the documentation to operate it. Each is delivered to a scope and a fixed price agreed in writing, in milestones that ship working software.
For specific ideas, the application catalog lists 427 applications by industry, business function and technology.
Document processing and extraction
Teams that receive documents from outside the company spend their day reading them and re-keying the contents. Volume grows faster than headcount, and errors surface downstream where they are expensive.
What the application does
- Reads scanned and digital documents, including handwriting and mixed layouts.
- Extracts the fields your process needs and validates them against your rules and your reference data.
- Routes clean records into your system of record and sends exceptions to a person with the source highlighted.
- Keeps every extraction traceable to the page it came from.
Technical approach
OCR and layout analysis combined with language models for extraction, deterministic validation against your business rules, and a review queue for anything below the confidence threshold you set.
What you provide
- A sample of real documents, redacted if needed
- The fields and validation rules your process uses
- Access to the destination system or an export format
What you receive
- A production application with an exception review screen
- Measured extraction accuracy on your documents
- Integration with your system of record
- Operating documentation
Knowledge assistant on your own documents
The same questions are answered from the same files every week, by the few people who know where to look. New staff take months to reach that point, and customers wait.
What the application does
- Answers questions from an approved corpus of your documents and nothing else.
- Cites the source passage for every answer, so the reader can check it.
- Respects the permissions of the person asking: a user sees only what they are allowed to see.
- Declines when the answer is not in the corpus, and routes the question to a person.
Technical approach
Retrieval-augmented generation over your documents with citation validation in application code, permission-filtered retrieval, and fail-closed behavior when the model cannot ground an answer.
What you provide
- The documents, in whatever form they exist today
- Who may see what
- A list of the questions people actually ask
What you receive
- A web application, chat interface, or integration into the tools you use
- An evaluation set and measured answer quality
- Permission-aware retrieval
- A content update process your team can run
Workflow automation with human approval
Requests arrive by email, portal and phone, get sorted by hand, and wait in queues. The sorting is predictable; the decisions at the end are not, and they are the part your staff should be spending time on.
What the application does
- Receives requests from the channels you already use and classifies them.
- Gathers the information needed to act, from your systems and from the requester.
- Prepares a recommended action with the evidence behind it, for a person to approve or change.
- Executes approved actions and records every step for audit.
Technical approach
Deterministic control flow with language models used for classification, extraction and drafting, confirmation gates before any consequential action, and full logging for review.
What you provide
- A description of the process as it runs today
- Access to the systems the process touches
- The rules for what may proceed without a person
What you receive
- A production workflow application with an approval queue
- An audit log of every automated and human action
- Measured turnaround before and after
- Operating documentation
Forecasting, risk and quality models
The data to anticipate a problem exists in your systems, and the problem still arrives as a surprise. Reports describe last month; nobody has time to build the model that would describe next month.
What the application does
- Trains on your historical data and produces predictions on a schedule or on demand.
- Delivers the results where decisions are made: a dashboard, an alert, a field in your existing system.
- States its confidence and the factors behind each prediction.
- Retrains as the data changes and reports when its accuracy moves.
Technical approach
Purpose-built classification and regression models evaluated against your metrics, with explainability on each prediction and drift monitoring in production.
What you provide
- Historical data and the outcome you want to predict
- Where the prediction needs to appear
- Who acts on it
What you receive
- A trained and evaluated model with documented results
- Integration into your reporting or operational system
- Monitoring for drift
- A retraining schedule
Computer vision for inspection, counting and monitoring
Someone walks the floor, the yard or the field and writes down what they see. The record is late, inconsistent, and depends on who was looking.
What the application does
- Detects, counts, measures and identifies objects, animals or people in images and video.
- Runs on a phone, an edge device or in the cloud, depending on connectivity and latency.
- Produces a structured record with a confidence level for every observation.
- Flags what needs a person's attention and leaves the rest to the record.
Technical approach
Object detection, tracking, re-identification and pose estimation models trained on your data, optimized for the target device, with the labeling pipeline delivered alongside.
What you provide
- Example images or video from the real environment
- The observations that matter and how they are judged today
- The devices or cameras in use
What you receive
- A production application, mobile or fixed
- Measured detection accuracy on your data
- Labeled datasets you own
- Operating documentation
AI features in your product
Customers ask when the product will have AI in it. The team that runs the product is fully occupied running it, and a feature that fails in front of customers costs more than one that never shipped.
What the application does
- Adds the feature inside your existing product, using your authentication, data model and design.
- Behaves predictably: grounded answers, bounded actions, and clear handling when the model is unsure.
- Scales with your usage and reports its cost per request.
- Ships with the evaluations, logging and guardrails a customer's security team will ask about.
Technical approach
Model integration behind your existing services, retrieval and tool use where the feature needs them, evaluation suites run on every change, and observability for cost, latency and quality.
What you provide
- Access to the product codebase or its APIs
- The feature as your customers have described it
- Usage and data volumes
What you receive
- The feature in production, with a staged rollout
- An evaluation suite and measured quality
- Cost and latency reporting
- Documentation for your engineers and your security questionnaire
Industries
The applications above are built for a process, and the process is specific to an industry. These are the settings DI-DS has delivered in or is equipped for.
- Healthcare operations
- Claims, clinical documents, prior authorization and scheduling, delivered inside HIPAA controls.
- Insurance and financial services
- Document intake, underwriting support, fraud and risk models, audit-ready logging.
- Agriculture and food
- Livestock and crop monitoring from phone and fixed cameras, records and traceability.
- Manufacturing and logistics
- Visual inspection, counting, demand forecasting and exception handling on the floor and in the yard.
- Professional services
- Contract and document review, knowledge assistants, client intake and reporting.
- Software companies
- AI features inside an existing product, built to pass a customer's security review.
Describe the process or product
A short written brief is enough. We reply by email with questions or a proposal and confirm scope and price in writing before work begins.