Custom knowledge tools for your team
On-device AI document assistant development
Build a native Apple document assistant with local retrieval and on-device generation, scoped to supported devices and your actual connectivity requirements.
Discuss your document assistantDocument evidence
Source passages
Where the workflow breaks down
Sensitive document workflows need explicit decisions about where processing and storage happen.
Agree the evidence and data boundaries
We define supported devices, languages, document access, retention and evaluation questions before implementation. Local inference and network-backed library sync are scoped separately.
What we build with you
- Assess device and model availability before implementation.
- Design local storage, indexing and generation paths.
- Separate local inference from authenticated download and sync requirements.
How we verify the workflow
- Test representative and unsupported questions.
- Inspect evidence and source references with your reviewers.
- Verify agreed failure, access and recovery scenarios.
Start with one document collection
- 01
Define the process
Map the records, roles and exceptions in your current process.
- 02
Build the agreed scope
Implement the agreed workflow and connections with reviewable records.
- 03
Test and hand over
Run representative scenarios, record results and train the people who use it.
Connected workflows
PDF OCR and document ingestion automation
Turn text PDFs and scanned pages into searchable document content with extraction diagnostics, indexing status and reprocessing workflows.
Hybrid search development for document libraries
Combine keyword matching and semantic retrieval to find useful evidence across manuals, policies and business document collections.
AI answers with document source citations
Develop source-linked document answers that let users inspect the passages and page references used to assemble a response.
Before we start
Can this work without a cloud AI service?
We can scope local retrieval and on-device generation for supported hardware. Authentication, downloads and synchronization can still require connectivity. We document these boundaries and test the agreed offline scenarios.
Can every answer be trusted automatically?
Source links help users review answers; they do not guarantee correctness. We agree evaluation questions, unsupported-answer handling and human review for consequential decisions.
On-device AI document assistant development
Describe your document workflow
Tell us which documents people search, which questions they ask and where the system must run.
- Document types, languages and approximate volumes
- Example questions and access requirements
- Target devices, integrations and connectivity needs