Virtual Assistant for AI Research Tool Owner

★★★★★ TRUSTED BY USA AI RESEARCH LABS

Build Better Models.
We Handle the Data.

Stop doing manual RLHF, dataset cleaning, and paper tracking. Access fully managed Virtual Assistants trained specifically to support AI researchers, data scientists, and ML tool founders.

train_pipeline_v4.sh
[10:41:02] Initializing dataset curation...
[10:41:05] VA_Agent parsed 14,205 rows (JSONL)
[10:41:08] Running RLHF manual evaluation pass...
[10:41:15] ✔ Quality thresholds met.
[10:41:16] Pushing dataset to Hugging Face Hub.
> _

Cognitive Operations Support

Building AI tools requires high-quality data and meticulous testing. Our VAs act as the human intelligence layer for your research pipeline.

RLHF & Model Evaluation

Providing Reinforcement Learning from Human Feedback. Manually reviewing model outputs, ranking responses, and tagging hallucinations to fine-tune your tool's accuracy.

Dataset Scraping & Cleaning

Gathering raw text, image, or audio data from target sources. Formatting, deduping, and structuring data into clean CSVs or JSONL files ready for model ingestion.

Literature & Paper Tracking

Monitoring ArXiv and research hubs for new papers matching your focus. Summarizing abstracts and compiling relevant methodologies into your Notion workspace.

API & Endpoint QA

Running systematic tests on your new tool's API endpoints. Logging latency, documenting edge-case failures, and creating structured bug tickets in GitHub or Jira.

Beta Tester Management

Onboarding researchers to your platform, managing Discord/Slack communities, collecting user feedback, and triaging feature requests for your engineering team.

Technical Documentation

Transcribing developer notes into polished API documentation, updating README files, and maintaining the knowledge base for your AI product's users.

Research Stack Integration

We assign VAs capable of operating within modern AI and data science environments.

Hugging Face
GitHub / Git
Jupyter / Colab
Vector DBs
Discord / Slack

The Rational Choice

Why researchers avoid generic freelancer networks.

Traditional Freelance Platforms
Sagedoer Managed VA
Budget Drain: Up to 40% lost in hidden platform markups and bidding fees.
Resource Efficiency: 0% hidden fees. Pay strictly for hours of pure output.
Time Deficit: Founders spend hours supervising data labeling and QA.
Managed Ops: Dedicated Project Manager supervises task execution for free.
Security Risk: Unvetted talent handling proprietary datasets or API keys.
Data Integrity: Internally vetted experts operating under strict confidentiality.

Research Pipeline Setup

Four simple steps to initialize your human-in-the-loop support.

01

Define Specs

Submit your specific tech stack and data needs via Email, Form, or WhatsApp.

02

Alignment

Your PM outlines a data handling strategy, selects the right VA, and finalises SOPs.

03

Execute

We handle the execution, cleaning datasets and evaluating outputs seamlessly.

04

Compute Cost

Pay exclusively for the VA's actual working time. PM supervision is 100% free.

Compute Bandwidth Pricing

Scale your research. Transparent USD pricing. Zero setup fees.

Part-Time Allocation
20 HOURS / WEEK
$7/hr
Est. $560 USD / Month (4 Weeks)
  • Pay only for pure output
  • Dedicated Project Manager included
  • Free management supervision
  • Zero setup or onboarding fees
  • No monthly membership charges
Initialize Setup
Max Compute
Full-Time Allocation
40 HOURS / WEEK
$6/hr
Est. $960 USD / Month (4 Weeks)
  • Pay only for pure output
  • Dedicated Project Manager included
  • Free management supervision
  • Zero setup or onboarding fees
  • No monthly membership charges
Initialize Setup

System Queries (FAQ)

How do you handle proprietary research data?

Data integrity is paramount. Our team is trained to never store sensitive datasets locally. We work entirely within the secure cloud environments or sandbox servers you provide, and all VAs operate under strict Non-Disclosure Agreements (NDAs).

Can VAs write production ML code?

Our VAs are specialized in *data operations* rather than core engineering. They excel at dataset formatting, RLHF, prompt testing, documentation, and managing research communities, allowing your actual ML engineers to focus on architecture and model training.

How does the Dedicated Project Manager work?

Your dedicated PM acts as your single point of contact. They understand your research protocols, delegate labeling tasks to the appropriate specialist in our team, ensure quality control, and deliver the final dataset to you—completely free of charge.

What if I need to replace a VA mid-project?

Because you work directly through your project manager, if a specific talent isn't a perfect fit or if someone takes time off, we handle internal replacements seamlessly. Your data pipeline is never disrupted.

Ready to Accelerate Research?

Stop cleaning datasets manually. Focus your expertise on model architecture and innovation. Establish a connection today.