Why we stay ahead

We define the test before we recommend the tool.

AnovaAI Labs documents the questions, methods, and review gates behind model, agent, and memory recommendations. Concept pages are clearly separated from validated client evidence.

Lab runtime
Research protocols and review gates.
prompt evals
memory checks
tool calls
Logged
Agent runs
Gated
Eval suites
Tracked
Models tested
Evaluation pipeline
Research to product signal
Illustrative
Retrieval rubricDefined
Tool-use checksPlanned
Latency measurementRequired
What We Do

Five research workstreams

A shared structure for framing questions, defining evidence, and recording limitations.

Research

Exploring new architectures, training methods, and model behaviors.

Development

Defining implementation patterns that can be tested against a concrete task.

Operations

Designing monitoring, permission, and review patterns for real workflows.

Experiments

Drafting testable protocols with declared inputs, measures, and limits.

Studies

Documenting methods and limitations before presenting a result.

Lab operating system

Each proposed experiment defines its measures before results are presented.

The method records task quality, reliability, latency, and review requirements so a recommendation can be evaluated against a real operating need.

Evals
Model behavior
Bench
Tool use
Concept
Cloud memory
Study
Weather signals
Focus Areas

What We're Researching

Questions organized across model, retrieval, hosting, and workflow topics.

Model Distillation

Studying compact-model tradeoffs across task quality, latency, and cost.

Model Training

Defining the data, holdout tests, and review gates required for domain adaptation.

Image & Video

Evaluating provenance, consistency, and review workflows for generated media.

Evaluation Tracking

Comparing public evaluations with declared models, tasks, and operating conditions.

Agentic Systems

Testing how tool-using agents prepare actions while preserving approval boundaries.

LLM & Chatbot

Studying source-grounded conversations for support, sales, and internal operations.

Small Language Models

Comparing compact local models with larger references on specific tasks.

Hosted Models

Reviewing hosting, privacy, observability, and throughput tradeoffs.

Task Models

Exploring narrow models for repeatable workflow steps with clear failure handling.

Featured

Flagship Projects

Research track

AnovaAI LLM

A research track for model selection, tool-use evaluation, source context, and reviewed agent actions.

Read more
How We Work

From question to evidence.

01

Research

We explore architectures, training methods, and model behaviors that matter.

02

Prototype

Rapid experiments and controlled trials let us test hypotheses fast.

03

Review

Candidate methods move forward only after evidence and approval gates are defined.

04

Document

Methods, operating conditions, and limitations are recorded when evidence is ready.

Explore the Labs

Every area of our research, all in one place.

FAQ

Questions About the Labs

What we do, how it works, and how you can get involved.

AnovaAI Labs organizes AnovaGrowth research questions and evaluation methods across models, retrieval, tool use, and reviewed workflows. Concept pages are not validated products or published benchmarks.
There is no standing public model catalog or preview program represented here. Contact us if you have a concrete task, dataset, or risk question that could support a scoped feasibility review.
The labs pages define questions and review gates that can inform client recommendations. A method should only be recommended when its evidence matches the client task and operating conditions.
No finished weather model or comparative accuracy benchmark is represented. The page describes questions a future evaluation would need to answer across regions, conditions, baselines, and uncertainty.
It is our subjective, internal assessment of how close current AI systems are to artificial general intelligence. It is not a scientific measurement, think of it as our team's informed perspective on where the technology stands today.
Use the contact page to propose a specific research question, dataset contribution, or protocol review. Feasibility and scope are confirmed case by case.

Research with a review boundary.

Protocols, evidence, and limitations should be documented before a method is recommended for real use. Bring us a concrete task and we will define what must be proven.