AI engineering contractor · commercial & SBIR/STTR · US-performed

Hand off the problem. We own the AI solution, end to end.

We train the model, adapt an open one, or build the whole system. You get the complete working solution, proven at every milestone. NeurIPS, ICML, and 146K lines of our own code in production.

Start a conversation See the work

Work

Products, benchmarks, papers, and code. All public, all linked.
UAV3D photorealistic aerial scene with five drones over a simulated city

Benchmark · NeurIPS 2024

UAV3D, a public large-scale benchmark for 3D perception from drone swarms

Detection, tracking, and collaborative perception from UAV platforms, in the nuScenes format.

  • 1,000 scenes · 500K RGB images · 3.3M annotated 3D boxes
  • Public code, dataset, and leaderboard
H. Ye · NeurIPS 2024, Datasets and Benchmarks track Project site →   ▶ Demo video
NovelHive: 200,000 words, 26 voices, 7 minutes
Live product

NovelHive, a consumer AI fiction platform on web and iOS

One prompt becomes a 200,000-word novel with a 26-voice audiobook.

Team · live since 2025 novelhive.ai →
Boston Dynamics Spot running our navigation policy, deployment code on screen
Robotics

Sim-to-real navigation on a Boston Dynamics Spot

Navigation policies trained in simulation, deployed zero-shot at 95% task success.

F. Liu · M.S. thesis, 2024 ▶ Watch the robot →
ACD-DETR detection results on UAV imagery
Peer-reviewed

ACD-DETR: small-object detection in drone imagery

H. Ye · Sensors, 2025 Read the paper →
MatchXML architecture diagram
Paper + code

MatchXML: classification over millions of labels

H. Ye · IEEE TKDE, 2024 GitHub →
DeepPhospho workflow figure from Nature Communications
Paper + code

DeepPhospho: deep learning for phosphoproteomics

F. Liu · Nature Communications, 2021 GitHub →
WeakNucleiSeg two-branch architecture with nuclei imagery
Paper + code

Nuclei segmentation from point annotations only

F. Liu · ISBI, 2022 GitHub →
Text-to-image synthesis comparisons on the CUB dataset
Paper + code

Contrastive learning for text-to-image synthesis

H. Ye · BMVC, 2021 GitHub →
Taxonomy diagram of LLM attacks and defenses
Survey

Vulnerabilities and protections in large language models

W. Liu · arXiv, 2024 Read the survey →
APLC-XLNet model architecture
Paper + code

Adaptive label clusters for extreme classification

H. Ye · ICML, 2020 GitHub →
GMMC t-SNE feature clusters
Peer-reviewed

Generative Max-Mahalanobis classifiers

H. Ye · ECML PKDD, 2021 Read the paper →
Adversarial RL feature selection framework
Peer-reviewed

Adversarial RL for unsupervised domain adaptation

H. Ye · WACV, 2021 Read the paper →
Multi-view 3D detection views on the UAV3D benchmark
Under review

PropBEV: temporal query propagation for multi-view 3D detection

H. Ye · under review, 2026 UAV3D benchmark →

Solutions

Every engagement ends in a fixed-price SOW with named deliverables and a date.

Prove your AI works

“The demo convinced everyone. Now the contract needs a quality number, and there's nothing behind it.”

We build the measurement first: LLM judges across model families, written up as acceptance criteria you can paste into a contract. On our own product it measured a 28% quality gain with real users.

In 2-4 weeks, you get:

  • Eval harness, wired into your CI
  • Scored baseline on your data
  • Acceptance criteria, contract-ready

The fastest way to start: a two-week fixed-price eval audit. Scope an eval audit →

YOUR SYSTEM JUDGE 1 JUDGE 2 JUDGE 8 8 JUDGES · 2 MODEL FAMILIES SCORE 15 DIMENSIONS DIVERGENCE FLAGGED BASELINE ACCEPTANCE +28%
TARGET BASE MODEL TUNED QUALITY TRAINING →

Get a model that does the job

“The hosted model is almost good enough, and prompt changes have stopped closing the gap.”

We post-train on your data with SFT, DPO, or RL, or adapt an open model you can self-host. Our policies ran a physical Boston Dynamics Spot at 95% task success.

In 4-8 weeks, you get:

  • Tuned weights, owned by you
  • Training code and data pipeline
  • Held-out evaluation report
Scope a training run →
VEHICLE 0.97 VEHICLE 0.91 TRACK 007 0.42 DROPPED

Make your system see

“Off-the-shelf detectors fall apart on our footage, and nobody in-house has done perception.”

Detection, tracking, and segmentation on your aerial, clinical, or industrial data. Published at NeurIPS, in Sensors, and as an ISBI oral.

In 6-10 weeks, you get:

  • Trained perception model
  • Validation study you can cite
  • Deployable inference pipeline
Scope a perception build →
BUILD CI TESTS ✓ PASS DEPLOY MONITOR KEEP IT RUNNING

Ship it and keep it running

“The last contractor emailed a zip file and left. It broke the first week real users hit it.”

The RAG or agent layer plus the backend, billing, and CI around it. We run this stack ourselves: novelhive.ai, live since 2025.

In 6-12 weeks, you get:

  • Live monitored deployment
  • Source repo, tests passing
  • CI gate on every deploy
Scope a production build →

Engagement

01

20-minute call

Tell us what you need. We will tell you honestly whether we can do it.

02

Fixed-price SOW

Two pages, on your template or ours. For SBIR/STTR we scope to your award's limits.

03

Milestone delivery

We invoice at each milestone, Net 30. All work is done in the United States.

FIXED PRICE · MILESTONE INVOICED · NET 30 M1 · invoice M2 · invoice M3 · invoice done
146Klines of code in production, novelhive.ai
3.3Mannotated 3D boxes, UAV3D benchmark
14publications, listed below
26voices per audiobook, NovelHive

Team

Technical Lead

Weizhen (Frank) Liu

LLM systems & production ML.

Nature Communications · ISBI · Microsoft Research alumnus
Research Lead

Hui Ye, Ph.D.

3D perception & computer vision.

NeurIPS · ICML · IEEE TKDE · Ph.D. CS
Chief Executive Officer

Maya Christine Liu

Contracting authority: contract administration, invoicing, compliance.

Publications

Tell us what's short-handed.

One paragraph from you. We reply with scope, price, and a delivery date.

Goes straight to our team. We reply within one business day.
NOVELA AI

Fixed-price AI engineering. Livermore, California.

Verify

Google Scholar UAV3D paper Nature Communications SAM.gov

Contact

[email protected] (678) 997-7619 How we engage
Novela AI LLC UEI (SAM.gov) J6U5C73EBW27 NAICS 541511 · 541512 · 541715 · 541519 Small business · California LLC 2025 Livermore, CA 94551