01
Assistants that know your business
Retrieval-grounded assistants that answer from your documents, product data and policies — with citations, so an answer can be checked rather than trusted blindly.
Services 01
AI Development & Integration
Custom AI applications connected to the systems you already use.
Most AI projects stall in the gap between a promising demo and a system people can rely on every day. We build the second thing. Intelligent assistants, document and data processing, retrieval over your own knowledge — wired into the CRM, ERP, ticketing or file storage your team already opens every morning.
- Starts with
- Prototype
- Timeline
- Weeks
- Pricing
- Phased
What this service commits to
- 3–5days
- To a working prototype
- 100%
- Answers carry sources
- 1
- Evaluation set
- 3
- Confidence outcomes
Against your data, on cases you already know the answer to.
Every claim links the passage it came from, or it is not shown.
Built from your real cases and agreed before launch.
Answer, hold for approval, or refuse and route to a person.
01Sound familiar?
You are probably here because of one of these.
- 01A pilot that impressed everyone and then quietly died.
- 02Knowledge that lives in PDFs, inboxes and one colleague's head.
- 03Answers that sound confident and are occasionally wrong.
- 04An AI tool your team has to leave their actual tools to use.
02What you get
What we actually build.
A working system in production, an evaluation set that tells you when it drifts, and documentation your own developers can pick up.
02
Document and data processing
Invoices, contracts, forms, tickets and email turned into structured records. Extraction with confidence scores, a human review path for the uncertain cases, and a straight-through path for the rest.
03
Integration into your stack
The model is a small part. The work is the connective tissue: authentication, permissions, rate limits, retries, audit trails and a place for the output to land in the system your team already uses.
04
Evaluation you can argue with
Before launch we build a test set from your real cases and measure against it. You get numbers, not adjectives — and a way to tell whether the next change made things better.
03Under the hood
What happens between the question and the answer.
Every demo shows the happy path. The value of a production system is what it does on the other two — which is why the confidence gate is the part we design first.
- 01
The question arrives
From a customer, or from your own team inside the tool they already use.
- 02
Retrieve, don't recall
Hybrid search over your corpus returns candidate passages, which are reranked. The model is never asked what it remembers.
- 03
Draft against the passages
The answer is composed only from what was retrieved, and every claim carries the passage it came from.
Confidence gate
set with you, per field or per intent
certainunsure
above threshold
Answered, with sources
Sent or shown directly, with citations a person can open.
near threshold
Answered, but held for approval
Drafted and queued. A person presses send until the numbers earn autonomy.
below threshold
Refused, and routed
It says it does not know and hands the case to a person. This is the path most implementations skip.
Bring us one ai development problem and we'll scope it live.
Free, 20 minutes, and you leave with a ranked shortlist either way.
04Build patterns
The shapes this usually takes.
Named patterns rather than a capability list, because the shape of the solution is what determines the cost and the risk.
Grounded answering
Hybrid retrieval over your corpus, reranking, answer synthesis with inline sources, and an explicit refusal path when the corpus does not contain the answer.
Human-in-the-loop extraction
Per-field confidence thresholds route low-certainty documents to a review queue. The queue doubles as training data for the next iteration.
Tool-using agents, scoped tight
Agents with a small, permissioned set of tools and a hard budget, rather than open-ended autonomy. Predictability beats cleverness in production.
Typical stack
- Python
- TypeScript
- LLM APIs & open models
- Vector search
- Queues & workers
- Postgres
05How it runs
Same three steps, every time.
You can stop after any step and keep what has been built.
- 01
Discover
20 minutesA short call to find where AI has the biggest leverage in your business.
- 02
Prototype
Days, not quartersA working proof of concept, so you decide on evidence rather than promises.
- 03
Ship & scale
WeeksProduction deployment, integration, and ongoing improvement.
06Frequently asked
AI Development, answered.
Something we have not covered? Ask us directly or mail hello@befzy.com.
Whichever the use case justifies. Commercial APIs are usually the fastest route to a strong first version. Open models running on European infrastructure become the better answer when data sensitivity, per-request cost or latency dominate. We benchmark both against your cases during the prototype rather than deciding on principle.
Three layers. Answers are grounded in retrieved passages rather than model memory, every answer carries its sources so a person can verify it, and the system is allowed to say it does not know — which is the layer most implementations skip. We then measure the refusal rate as carefully as the accuracy rate.
Yes, at a cost in model quality that we will quantify rather than hand-wave. Fully self-hosted setups are practical today for retrieval, classification and extraction. For open-ended generation the strongest models are still hosted, so we scope what actually needs to be sent and what can stay inside.
Usage exposes cases your test set did not contain. We keep the evaluation set growing from real traffic, review the failures with you, and iterate. Most systems get meaningfully better in the six weeks after launch, which is why we prefer a narrow first release.
07Also from the studio
Next step
Let's see whether ai development is your highest-leverage move.
A free 20-minute call, no strings attached. We will tell you where the leverage is — and where it is not.
- No sales deck, no discovery invoice
- You get a ranked shortlist either way
- If AI is the wrong tool, we say so