01
Capability is abundant
Frontier and open models are strong enough to matter. Access alone is no longer the scarce resource.
Born · Applied model programme
Applied intelligence, built to ship.
Born turns model capability into usable systems — adapted weights, shaped data, honest evaluation, and workflows that survive contact with real work. Born-9B Preview is the first public proof.
Current releasePromoted
CHECKPOINT
Born-9B Preview v2
LOCAL GATE
0.9244 · 23 / 25 pass
SWE PROXY
0.8559
ADAPTER
rk500/Born-9B-Qwen3.5-9B-Preview
BASE
Qwen/Qwen3.5-9B · QLoRA SFT
Thesis
Raw model access is not the product.
Most organizations do not need another keynote about AI. They need systems that work under messy data, domain constraints, limited budgets, and the demand for repeatability.
02
Applied intelligence is scarce
Useful systems need task framing, domain data, honest evals, and deployment discipline — not another wrapper.
03
The gap is adaptation
Born exists to close that gap: tune, measure, document, ship. Proof over pitch.
04
Born-9B is evidence
The first public signal. A release with gates, caveats, and a Hugging Face adapter people can inspect.
What Born is
An applied AI programme that ships artifacts.
Born sits inside LeemerLabs as the model factory: adaptation, datasets, evaluation, agents, and the infrastructure path to production. It is not a side chatbot feature.
Explicitly not
A generic chatbot brand
A vague innovation studio
Consulting with no technical artifacts
Benchmark theater
A front-end wrapper pretending to be a model company
A one-model brand locked to one parameter count
Surfaces
One programme. Five working surfaces.
Release, chat, eval, research, and services — each with a job. Nothing thin. Nothing competing for the same story.
01
Born-9B Preview
LIVECoding-agent LoRA on Qwen3.5-9B. Promoted checkpoint v2, public adapter, full release dossier.
0.9244 weighted / 23 of 25 local gate / 0.8559 SWE proxy
Open the dossier02
Born Chat
OPENThe public workbench: live Born lanes, comparison models, quotas, and a training-loop notice that stays honest.
PromptKit UI · model switching · usage windows
Open experimental chat03
BornBench
OPENEvaluation harnesses and held-out gates that keep release claims tied to scored artifacts.
Methods, answer sheets, scored result files
Open BornBench04
Research & method
PUBLICCompany context, six-step method, eval systems, and the model arc — one surface instead of thin stubs.
Frame → Baseline → Data → Adapt → Evaluate → Operationalize
Read research05
Services
COMMERCIALModel adaptation, dataset engineering, evaluation systems, agent workflows, GPU training and inference setup.
hello@bornai.io · scoping within one working day
Open servicesMethod
Six steps. No theater.
The same loop for public releases and client work: frame, measure, data, adapt, evaluate, operationalize.
Full research & method01
Frame the task
Define the behaviour, constraints, and evidence that would make a custom model useful — before touching weights.
02
Baseline honestly
Measure the open base under the same gate you will use later. No silent goalpost moves.
03
Build the data
Create, clean, license, and split the examples that carry the domain into training. Provenance first.
04
Adapt the model
LoRA, QLoRA, distillation, or full tuning against an appropriate open base. Recipes you can audit.
05
Evaluate under load
Held-out gates, proxy packs, task harnesses. Claims stop where the scores stop.
06
Operationalize
Package adapters, document failures, hand off deployment — chat, API, or private endpoint.
Capabilities
Not just one model. A working applied stack.
Model adaptation
LoRA, QLoRA, continuation runs, and release packaging built around task fit rather than generic tuning claims.
Dataset engineering
Synthetic generation, teacher distillation, provenance, splits, and validation before a row reaches training.
Evaluation systems
Local held-out gates, proxy issue-resolution packs, BornBench lanes, and release rules that stop claims outrunning evidence.
Agent workflows
Tool-use closure, verification loops, repo-aware repair, and the operational glue around the model itself.
From the lab
Notes, releases, and what is moving.
01
Launch
17 May 2026 / 14 min
Born-9B Preview is finally here
The launch note for Born-9B Preview: Repath at the controls, GPT-5.5 Codex managing the run, the datasets, failures, benchmarks, and the public adapter.
02
Launch
17 May 2026 / 7 min
Born Chat is open: PromptKit UI, live model lanes, and the public training loop
What shipped in Born Chat, how the Born and comparison lanes are organized, why the training notice is explicit, and what Born Chat Pro is meant to become.
03
Systems
15 May 2026 / 11 min
Why Codex GPT-5.5 Operated Born-9B
The operating model behind the run: Codex GPT-5.5 High, Repath Ray Khan at the controls, and a model release managed through evidence, caveats, and repository state.
04
Essay
14 May 2026 / 6 min
How Born-9B Learned to Breathe
The origin story of Born-9B told from the real notes: the cheap first run, the honest tie, the many teachers, and the million-token second inhale.
Use the system
Chat the live lanes. Then read how they were built.
Try Born Chat, inspect the Born-9B dossier, or write about a scoped adaptation job. Show the artifact. Show the process. Avoid unsupported superiority claims.