Hi, I’m Halil.

I build practical AI for teams.

Turkish NLP models, privacy tools and AI workflows built around your own data.

  1. Your data
  2. Privacy
  3. Workflows
  4. Measure

What I help with

Teams

AI adoption for teams

Choose the right task, build a pilot and measure the result.

Read the roadmap

halil@halilneed.agency

Tell me what your team does today and where it gets stuck.

Models

Four small models for Turkish text: three for personal data, one for prompt injection. Run them locally; explore their weights, benchmarks and demos.

Turkish privacy and safety models

Masking, classification and the benchmarks behind them.

All models
halilneed/turkish-pii-detection Mask names, ID numbers, IBANs and contact details with a Turkish instruction. Text generation270M parametersUpdated 5 Oct 20262.4k downloads1 likes 0.944exact match, 1,000 rows halilneed/turkish-kvkk-classifier Classify Turkish text across 24 VERBİS and KVKK personal data categories. Text classification110M parametersabout 22 ms per textUpdated 2 Oct 202625 downloads1 likes 0.878micro-F1, 987 held-out texts halilneed/turkish-bseby-classifier Identify five banking data classes for inventories and DLP workflows. Text classification110M parametersabout 32 ms per textUpdated 2 Oct 202620 downloads 0.960micro-F1, 747 held-out texts halilneed/turkish-prompt-injection-classifier Flag prompt injection in Turkish text before it reaches an LLM, including encoded and hidden instructions. Text classification307M parametersabout 35 ms per textUpdated 14 Oct 202634 downloads 13/13encoded attacks caught, 1% false alarms on 2,875 benign texts

Evaluation sets and demo

halilneed/turkish-kvkk-classification-benchmark Dataset987 gold texts24 labelsCC0103 downloads halilneed/turkish-bseby-classification-benchmark Dataset747 gold texts5 labelsCC066 downloads halilneed/turkish-prompt-injection-false-alarm-benchmark Dataset2,875 benign textsfalse alarmsCC033 downloads halilneed/turkish-pii-detection-demo SpaceMask your own text in the browserruns on your device halilneed.agency/masking-tool Browser toolMask TCKN, IBAN, phone and email before text goes to an AI toolreversible labels

One input, three instructions

The PII model reads an instruction and a text, and writes the text back with the requested fields replaced by labels. The same weights mask everything, only the fields you name, or everything except them.

Instruction

Metindeki tÞm kişisel verileri uygun etiketlerle maskele.

Input

mÞşteri Ayşe YÄąlmaz tc 12345678901 tel 0532 111 22 33 e-posta demo@example.com.

mÞşteri [AD] tc [TCKN] tel [TEL] e-posta [EMAIL].

Recorded outputs of turkish-pii-detection v02 on CPU. The person and the numbers are made up.

How the PII model got to 0.944

A 270M model improved from 0.740 to 0.944 exact match with targeted synthetic data and averaged weights. Read the training notes for the recipe and failure cases.

Exact match on the public 1,000-row benchmark
  1. Starting model0.740
  2. v010.882
  3. v020.944
On the 531 rows I kept out of model selection, v02 scores 0.945. The weakest slice is text that mentions several people, at 0.750.

Tools

Open-source tools, mostly for people who work with coding agents.

Node.json npm

agentmemora

A local dashboard that reads session transcripts, auto-memory and instruction files to show what your agents know, flag context at risk, and move context between sessions, machines and agents.

GitHub

MCP server

solostacks

Pulls live data from Reddit, GitHub Trending and Hacker News and recommends tools for solo developers.

GitHub

Agent skill19 rule files

hyperframes-agent-skill

Teaches a coding agent to write correct HyperFrames (HTML-to-video) compositions.

GitHub

Browser quiz3 languages

promptrank

Five prompt scenarios, scored on clarity, creativity, technical depth and strategy. In Turkish, English and Spanish.

GitHub

Kits

Ready-made kits for legal, compliance and AI security teams. About the legal and compliance kit.

Test pack$39

Prompt Injection Test Pack

Ready-to-run attack prompts for LLM apps and agents (direct, indirect, encoded and hidden-Unicode cases), a scoring sheet and a remediation checklist.

Gumroad

Guides

Four interactive AI guides for teams, available in English and Turkish with PDFs.

Guide 34 stepsKVKK

Personal data and AI

What to classify, mask and keep in-house before text reaches a model.

Try it

Writing

I write on Medium about what the logs and benchmarks show.

About

I work in data analysis, product management and software in Istanbul. I build Turkish privacy models and open-source tools for coding agents.

The models, tools and articles here share benchmarks, evidence and known limitations.

Email
halil@halilneed.agency
GitHub
github.com/halilneed
Hugging Face
huggingface.co/halilneed
Medium
halilneed.medium.com