Grounded, cited, safe
Assistants that answer from your data and know when to stop.
Customer and employee assistants built on your documents and systems, with citations, permission-aware retrieval and hand-off to people.
Who it is for
Support, HR, operations and product teams with knowledge locked in documents.
Usually built with
- Anthropic API (Claude)
- OpenAI API
- RAG pipelines
- Embeddings & vector search
- pgvector
- Python
- Next.js
Approach
What we have learned building these.
The difference between a demo chatbot and a useful assistant is retrieval quality, permissions and evaluation. We build all three before we worry about the conversation design, and we measure answer quality on your real questions every release.
What matters
The features that decide whether it works.
RAG over your sources
Documents, tickets, wikis, databases; hybrid retrieval.
Permission-aware
Answers only from what the asker may read.
Citations & confidence
Every answer shows its source or defers.
Hand-off & actions
Escalate to a person; take approved actions with audit.
Evaluation dashboard
Quality tracked on real questions, every release.
Architecture
Assistant architecture
Sources
- Documents
- Tickets & wiki
- Systems of record
Retrieve
- Chunk & embed
- Hybrid search
- Permission filter
Reason
- LLM (provider-agnostic)
- Approved tools
Deliver
- Chat / Slack / Teams
- Review queue
- Evaluation & logs
Services involved
AI Development
Assistants, enterprise search, RAG, document processing and workflow agents built on your data and your systems, with evaluation, safety and human approval designed in from the first prototype.
Enterprise Search
Hybrid search over documents, tickets and systems with identity-aware filtering and citations.
System Integration
REST and SOAP APIs, webhooks, file and SFTP exchanges, event-driven architectures and middleware connecting ERP, CRM, payment, banking and SaaS systems, with monitoring that tells the business what failed.
Common in
Education
Learning platforms, admissions and student services, staff workflows and integrations with SIS and LMS systems.
Professional Services
Client portals, time and resourcing tools, knowledge assistants and automation for firms that sell expertise.
Technology & SaaS
Product teams, feature delivery, platform work and AI capabilities for startups and software companies.
Building a ai assistant?
Tell us about the users and the first version. We will suggest the architecture and a path to a working product.