The problem
What slows you down, and what we change
Today
- Choosing the wrong vector engine means a migration and extra costs when volume grows.
- A homegrown RAG pipeline can cost 10 to 70 k€ and months of development before you see a reliable result.
- Unsourced or hallucinated answers in production, that's lost trust you'll never win back.
With Buildoto
- The right engine for your stack and volume: pgvector or Vectorize, chosen on concrete criteria, not by dogma.
- The pipeline is already built and in production: {{prix:chatbot_rag}} excl. tax as a fixed price, delivered in 2 to 4 weeks, no subscription.
- Every answer cites its source, and the architecture is designed for your team to take over.
Supabase (pgvector), ideal if your data already lives in PostgreSQL: you keep everything in a single database (documents, metadata, vectors, multi-tenant RLS), classic SQL queries + vector search in the same place. The right default for most SaaS.
Cloudflare (Vectorize + Workers AI + R2), ideal for a 100% edge pipeline: upload to R2, extraction and embeddings in a Worker, Vectorize index, low latency worldwide, controlled costs. Relevant when volume is high or global latency matters.
Both together, a common pattern: Supabase for application data and auth, Cloudflare at the edge for ingestion and delivery. I decide case by case based on your constraints (existing data, volume, confidentiality, budget).
The criteria that tip the balance
- Existing data: already in PostgreSQL → pgvector, without a new building block to operate.
- Multi-tenant: per-client isolation required → pgvector + RLS, the filtering is structural, not application-level.
- Volume: up to a few hundred thousand vectors, pgvector holds up very well with an HNSW index; beyond several million or in multi-region, Vectorize takes the edge.
- Global latency: users on several continents → Vectorize at the edge, no round trip to a single region.
- Operating cost: both stay under a few dozen euros per month for SMB usage; the main line item is the generation API, not the vector database.
The packaged offer
The complete pipeline (ingestion, chunking, embeddings, hybrid search, citations) is already built and runs in production on beforbuild.com. I deploy it on your stack, pgvector or Vectorize, from €2,640 excl. tax as a fixed price, live in 2 to 4 weeks:
- Indexing of your documents and chunking tuned on your real content.
- Sourced answers, "no proof, no answer" clause, tested on your business questions.
- Integration on your channel (app, site, intranet, Slack) and documentation your team can take over.
The feature detail is on the Chatbot on your documents page.
Deliverables
What you get, in production
Proof in production
This feature already runs on beforbuild.com
Method
Audit → Build → Production
- 01
Free audit · 30 min
I embed in your context: mapping of your processes, your subscriptions and your vendor dependencies. No commitment.
- 02
Fixed-price quote
Scope priced on portable building blocks: feature to deploy or subscription replacement. Price and scope signed within 48 h.
- 03
Deployment & handover
I build it, deploy it in your environment and document it. You own the code and keep control of your data.
Book
Your free audit · 30 min
Pick a slot. We audit your case and you leave with a fixed-price quote.
FAQ
Frequently asked questions
Who I am
A single point of contact, from audit to handover
I design, develop and run my own features in production: BeForBuild.com, the B2B SaaS I manage single-handedly, is the proof. These proven building blocks, I deploy them in your environment, at a fixed price, and you own them.
You talk directly to the person who delivers: no subcontracting, no agency layer. The one who designs is the one who codes, deploys and hands over.
Stack & intégrations
Let's talk about your project
30 minutes to scope your need and quote the fixed price, no subscription. 6-month guarantee included. Reply within 24h.
Book my free audit · 30 min