Free RAG Search Engine — Included With Every BPO Option

"Your Customers Type What They Need and Your Search Returns Nothing Useful."

Keyword search matches words. It fails the moment a customer types something slightly different from what's in your documents. The Free RAG Search Engine understands what they mean — not just what they typed.

What does "RAG" mean?

Retrieval-Augmented Generation. Plain English: before answering, the AI looks up the answer inside your actual documents — your policies, your scripts, your product list — instead of guessing. It only tells the customer what is in your files. Nothing invented. Nothing hallucinated.

See the Live Demo → Send Us 100 Records — Free Test

The Problem

Keyword search works at 100 records. It breaks at 10,000.

At 10,000 products, keyword search returns noise. At 100,000 — users give up and call your support team instead. Your support team is answering search questions. That is not a people problem. It is a search problem.

Query Keyword search returns RAG search returns
"quiet dishwasher" Noise
Every product containing either word. 200+ results, most irrelevant.
Intent matched
The 3 models rated lowest for operating noise in your catalog.
"maternity leave" Noise
Every document containing those words. Staff reads through 40 pages to find the answer.
Intent matched
The exact policy clause with number of weeks and eligibility rules.
"force majeure construction contract 2023" Noise
400 documents. Attorney manually reviews to find what is legally relevant.
Intent matched
The 5 clauses that are directly legally relevant to the query.
"software engineer Bangkok 3 years" Noise
Every job with any of those words. Misses jobs titled "Developer" or located in "กรุงเทพ".
Intent matched
Software engineering roles in Bangkok, ranked by relevance to 3 years' experience — in any language.

The Daily Cost

Broken search is expensive — you just can't see the invoice

On Hold Right Now

Your staff spends 20 minutes manually looking up answers during live customer calls. The customer is on hold. The agent is searching. The call log shows "hold: 18 minutes."

That is not a call center problem. That is a search problem. The agent is not slow — the search is broken. RAG search in co-pilot mode returns the answer on the agent's screen in under 2 seconds. The hold time disappears.

Silent Abandonment

Your customers leave your product page when the search returns the wrong items. They do not call to complain. They go to a competitor whose search works.

You never see this in your analytics — it shows as a bounce. The lost sale is invisible. The only thing visible is that conversion on search results is lower than it should be. The fix is the search engine, not the products.


It's Already Running Live

RAG search on 4,190 jobs, 13 countries, 30 languages — test it now

RAG search loads your documents and data once — products, policies, listings, records, anything — and returns meaning-matched results on every query. Not by keywords. By meaning.

Live Demo — JobFreelanceThai.com Search

4,190 jobs. 13 countries. 30 languages. Searched by meaning, not keywords. Type a natural language query: "software engineer Bangkok 3 years" or "remote marketing manager Southeast Asia" — and watch what comes back. This is the same engine we deploy on your data.

Open Live Demo →

Opens jobfreelancethai.com/search.html in a new tab. No signup required.


What You Get

One engine. Any data. Any industry.

The technology is industry-agnostic. Only the data changes.

Semantic Vector Search
Users find what they mean — not just what they typed
Voyage AI voyage-large-2 embeddings (1536 dimensions) — state of the art for semantic retrieval. Your documents are loaded once. Every query returns meaning-matched results in milliseconds. One-time setup cost. Sub-millisecond retrieval at any scale. No degradation as your data grows.
Any Corpus, Any Industry
Product catalog. Policy library. Legal documents. Job listings. Anything.
BPO call centers, auto parts retailers, law firms, hospitals, e-commerce companies, real estate portals, government ministries. The engine does not care what industry you are in. You provide the data — call scripts, policy PDFs, product spreadsheets, FAQ documents, training manuals. We load it and deploy the search interface. The only thing that changes between clients is the data.
30 Languages
Search in Thai. Return results in English. Score in Filipino.
A single query crosses any language barrier. Your Thai customer types their query in Thai — the engine finds the best match across all your documents regardless of the language they were written in. Fully operational across all 30 languages used on the JobASEAN platform today.
Real-Time Co-Pilot
The answer appears on the agent's screen before they have to say "let me check"
In co-pilot mode, the customer is on the phone with your agent. Maya listens (via voice channel) and simultaneously searches your internal documents and policies based on what the customer is asking. The answer appears in under 2 seconds — no hold time, no manual lookup. Works identically on text channels: WhatsApp, Viber, LINE — Maya searches on every message.
AIVA Evaluation on Every Result
Not just search — scored search
Every item returned by the search can be scored for fit. A product is scored for match to the customer's stated need. A policy clause is evaluated for relevance to the customer's query. A candidate is scored against the job description. The search returns results. AIVA evaluates them. You see both — ranked, not just listed.
Full Web Development Included
We build the front end alongside you
Corpus ingestion, pgvector deployment, API key scoping, result card template, search interface, hosting — all included in every deployment. You do not need a development team on your side. Vaughn and Claude build the front end together using the full JobASEAN stack: static HTML/CSS/JS, FastAPI, Supabase pgvector, Docker + Traefik, Cloudflare.

Proof of Scale

Running live, right now — test it before you commit to anything

4,190
Jobs indexed across 13 countries — searched live at jobfreelancethai.com
30
Languages — query in any, return results from any
1,536
Embedding dimensions — Voyage AI voyage-large-2, state of the art for semantic retrieval
<50ms
Search response time — Supabase pgvector HNSW index, no degradation at millions of records
Cost per query: negligible. Embedding is a one-time cost per record at ingestion. Search is sub-millisecond per query. The operational cost of RAG search at typical business volumes is a rounding error compared to the cost of broken keyword search.

Common Questions

Two questions we hear every time

"This won't know our specific products or terminology."
RAG search is trained on your data, not general knowledge. Your product catalog, your documents — that is what gets searched. Your terminology is what gets indexed. The engine searches what you feed it — nothing else. A query for "high-torque 18V cordless drill" searches your drill listings, not the internet. If it is in your data, it gets found. If it is not, nothing is invented.
"We already have search. Our platform vendor built one."
Keyword search is a feature. RAG search is a different technology. The test is simple: go to your search and type a natural language query — "quiet under-counter dishwasher for a small kitchen." Count how many of the top 10 results are actually relevant. Then test jobfreelancethai.com/search.html with a natural language job query. The difference is the answer.

Pricing

Free RAG Search Engine with every BPO Option. Standalone for everyone else.

If you are already on any BPO option — the Free RAG Search Engine on your data is already in your plan. No extra line item. No separate quote. Send your documents and we index them as part of your deployment. If you only need search — no voice, no AI hiring tools — there is a standalone track below.

What developers charge to build this
$19,000 – $48,000
typical agency quote for a custom vector search build
Document ingestion pipeline
$3,000 – $8,000
Embedding model integration
$2,000 – $4,000
pgvector + HNSW index setup
$2,000 – $5,000
Search API layer
$4,000 – $10,000
Search front-end UI
$3,000 – $8,000
Hosting + infrastructure
$2,000 – $5,000
Plus ongoing maintenance: $800 – $2,500/month
Why it costs that much
Vector search is not keyword search with a library swap. It is a full engineering project across six disciplines that most web developers have never touched:
1. Chunking strategy — how documents get split before indexing. Wrong chunking = poor results. Most builds fail here first.
2. Embedding models — Voyage AI and OpenAI embeddings require API expertise and configuration not covered in standard dev tutorials.
3. pgvector + HNSW — a specialized PostgreSQL extension with a vector index. Rare skill. Most web developers have never deployed one.
4. LLM layer on top — semantic results need a language model to surface the right answer. Without this, you have fast search but not useful search.
5. Multilingual embeddings — supporting 30 languages is not translation. It requires multilingual embedding models and query routing logic.
6. Infrastructure at scale — Docker, Traefik, Cloudflare, rate limiting, API key scoping — six more disciplines beyond the search itself.
Why we give it free with every BPO option
Already built and running. The infrastructure behind jobfreelancethai.com/search.html is live and proven. Adding a client's documents is a deployment task — not a new build.
Infrastructure cost is negligible. Embedding your documents costs under $5 one-time. Monthly search cost is under $0.50. We absorb it. The value delivered is orders of magnitude higher.
Vector search is not common. Most vendors do not have this. Bundling it as standard makes every client's deployment dramatically more capable — and that is a competitive advantage for them and for us.
Track 1 — Already in your plan (Options A, B, C, D, E)
What's included
  • Your documents loaded at deployment
  • Policy docs, FAQs, call scripts, catalogs
  • Co-pilot: answer appears on agent screen
  • Search across all active channels
  • 30 languages — query in any, return in any
  • Web front end built and hosted
What you provide

Your documents — any format your team already has them in. Examples:

  • Agent call scripts and escalation guides
  • HR and leave policy PDFs
  • Product catalogs and pricing sheets
  • FAQ documents and knowledge base articles
  • Training manuals and SOP documents
  • Legal contracts or compliance documents

Your deployment partner handles the submission as part of your onboarding. Nothing technical on your side.

Extra cost
$0

RAG search is bundled into every BPO option at no additional charge. It is part of how Maya works during calls and on text channels — not a separate product. The infrastructure cost per client is under $20 total. We absorb it.

Track 2 — Standalone (search only, any industry, no voice or hiring tools)
What standalone includes
  • Corpus ingestion + Voyage AI embedding
  • pgvector deployment + HNSW index
  • Search interface built to your branding
  • API key scoping + rate limiting
  • Hosted on the JobASEAN stack
  • Full web front-end development
Customization

The search engine and infrastructure are already built. What changes per client is the front end: your name, your logo, your result card layout, your color scheme.

Customization is scoped per project. Basic customization — name, logo, colors, result template — is a straightforward engagement. Larger customizations (multi-language UI, custom scoring layers, API integrations) are quoted separately.

How to start

Send us 100 records from your data — CSV, JSON, PDF, or a spreadsheet export. We index them, run sample queries, and send back a demo within 48 hours. Free. No commitment. No pitch deck. You see exactly what your users would see before agreeing to anything.

Send 100 Records — Free Test →

Send us 100 records. We'll show you what RAG search returns on them.

Any format. Any industry. We index your sample, run real queries against it, and send back the results within 48 hours. You see exactly what your customers or staff would see — before committing to anything.

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