Web App & SaaS Development · AI-Powered Web Apps
Semantic Search & Knowledge Base
Semantic search indexes your documents and answers natural-language questions, for support teams, internal knowledge or customers.
By Dilawar Khan · Updated
What semantic search & knowledge base includes
- Document indexing
- Natural-language search
- Answer with citations
- Access control
Technology
Built with Next.js, React, TypeScript, Tailwind CSS, Node.js, Supabase, PostgreSQL, pgvector. Server-rendered pages for search and AI crawlers, hosted on Vercel or your own infrastructure, with the code in your repositories.
What drives the cost
- Document volume
Related case study
Multi-tenant SaaS · Canada
SpidNums
Live SaaS product serving accounting firms in Canada (no usage figures published).
How a project runs
- Step 1
Share your project
Send a short note on what you want to build, who it is for and when you need it, through the contact page or by email.
- Step 2
Get a plan
You get a reply with questions, a suggested approach and technology, a timeline broken into milestones, and a quote.
- Step 3
Build in milestones
Work ships in small milestones you can review and test, with regular updates, so there are no surprises at the end.
- Step 4
Launch and support
The product goes live, code and accounts are handed over to you, and ongoing support is available if you need it.
Questions
Can access be restricted by role?
Yes; results respect the same permissions as the documents.
Will the AI make things up?
Less, when it answers only from retrieved documents and declines when it has nothing; we build that in and measure it.
MVP first or full product?
MVP first: 4–8 weeks to a version real users can pay for, then iterate. A full platform is 12–20 weeks.
Have a project in mind?
Tell me what you want to build. You get a reply within a few hours, 7 days a week, with questions, an approach and next steps.