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Research assistants

Search papers and reports, kept private.

Unpublished results are the most valuable thing a biotech owns, so they cannot go into a public chatbot. We build assistants on open-source models served where you choose, grounded in the papers and reports you give them, that quote their sources and say when they do not know.

// what matters here

What is different in this industry.

01

Your data stays yours

The model runs on GPUs set up for you. Nothing is sent to a public service or used to train anyone else's model.

02

Answers with sources

Every answer quotes and links the passage it used, so a scientist can check it in seconds.

03

Tested on your questions

A set of your scientists' real questions is run before every change, and the results kept.

04

A reading aid, not a scientist

It finds and summarises. It does not make scientific, clinical or medical judgements.

// example projects

Priced examples for this service.

Each one is hypothetical, labelled as such, and priced live from our rate card. Open any of them in the estimator and make it yours.

Example projectWeb appAIOpen-source model

Literature assistant on a private model

Hypothetical. Not a client, not a result.

// The problem

A biotech's scientists spend hours each week searching papers, patents and their own internal reports, and the company will not paste unpublished work into a public chatbot.

// What we would build

A literature assistant on an open-source model that runs on GPUs we set up for you, so nothing leaves your control. It searches the papers you choose, your internal reports and your notebook exports, answers with the passages it used, and says when it does not know. It helps your scientists read; it does not make scientific or medical judgements.

// What is in it

  • An open-source model served on GPUs set up for you, never a public chatbot
  • Search across papers, patents, internal reports and notebook exports
  • Answers that quote and link the passages they used
  • Access by role, so confidential programmes stay with their teams
  • A set of your scientists' real questions, run before every change

// Stack

  • Python
  • Open-source LLM
  • PostgreSQL with pgvector
  • Next.js
  • DigitalOcean GPU Droplets

// estimate

Build
≈ US$97,300 to US$149,000, delivered within 20 weeksCAD 138,500 to 211,600
Hosting
≈ US$4,360 a monthCAD 6,210 a month
Support
≈ US$2,500 a monthCAD 3,565 a month

Prices in your currency are estimates from today's Bank of Canada rate. All invoicing is in CAD or USD.

AI route
Open-source model
Model running cost
≈ US$4,190 a monthCAD 5,960 a month

Timeline by milestone

Discovery
2.9 to 3.4 weeks
Specification and evaluation plan
0.4 weeks
Design approved
2.4 to 3.4 weeks
Core features
1.4 to 1.9 weeks
Full build
0.9 to 1.4 weeks
Working pilot
2.9 to 5.4 weeks
Testing and fixes
0.9 to 1.4 weeks
Launch
0.9 to 1.4 weeks
Production
0.9 to 1.4 weeks

Outside our hands, and added to the calendar

Test access to your ELN or LIMS
1 to 4 weeks

How it is paid

Deposit 20%
CAD 27,640 to 42,260
Discovery 2%
CAD 2,764 to 4,226
Specification and evaluation plan 10.3%
CAD 14,234.60 to 21,763.90
Design approved 2%
CAD 2,764 to 4,226
Core features 6%
CAD 8,292 to 12,678
Full build 4%
CAD 5,528 to 8,452
Working pilot 31.1%
CAD 42,980.20 to 65,714.30
Testing and fixes 2%
CAD 2,764 to 4,226
Launch 2%
CAD 2,764 to 4,226
Production 10.6%
CAD 14,649.20 to 22,397.80
Holdback, 30 days after launch (10%)
CAD 13,820 to 21,130
GPU time for training and testing, at cost
CAD 300. Billed up front, at cost, outside the milestones
Example projectWeb appAIFrontier model

Contract lab portal for sponsors

Hypothetical. Not a client, not a result.

// The problem

A contract research lab takes study requests and sends results by email, sponsors in several countries ask the same status questions every week, and the lab's site does not look like the work it does.

// What we would build

A sponsor portal designed for your lab: sponsors submit requests, track their samples and studies, and download reports, with a help centre and an assistant that answers from it in the languages your sponsors use, handing anything about a study to your project managers.

// What is in it

  • A portal and site designed around your lab's brand
  • Study requests, sample shipments and status in one place for each sponsor
  • Reports released by your team, downloaded by the sponsor
  • A help centre in several languages, with an assistant that answers from it
  • Anything about a specific study handed to a project manager

// Stack

  • Next.js
  • Claude API
  • PostgreSQL with pgvector
  • Headless CMS
  • AWS Canada (Central)

// estimate

Build
≈ US$149,000 to US$228,000, delivered within 28 weeksCAD 212,400 to 324,800
Hosting
≈ US$218 a monthCAD 310 a month
Support
≈ US$2,500 a monthCAD 3,565 a month

Prices in your currency are estimates from today's Bank of Canada rate. All invoicing is in CAD or USD.

AI route
Frontier model
Model running cost
≈ US$42 a monthCAD 60 a month

Timeline by milestone

Discovery
2.9 to 3.4 weeks
Specification and evaluation plan
0.4 weeks
Design approved
6.4 to 11.4 weeks
Core features
1.4 to 2.4 weeks
Full build
0.9 to 1.4 weeks
Working pilot
3.9 to 6.9 weeks
Testing and fixes
1.4 to 1.9 weeks
Launch
0.9 to 1.4 weeks
Production
0.9 to 1.4 weeks

Outside our hands, and added to the calendar

Test access to your ELN or LIMS
1 to 4 weeks

How it is paid

Deposit 20%
CAD 42,480 to 64,960
Discovery 2%
CAD 4,248 to 6,496
Specification and evaluation plan 10.2%
CAD 21,664.80 to 33,129.60
Design approved 2%
CAD 4,248 to 6,496
Core features 6.2%
CAD 13,168.80 to 20,137.60
Full build 4.1%
CAD 8,708.40 to 13,316.80
Working pilot 30.7%
CAD 65,206.80 to 99,713.60
Testing and fixes 2%
CAD 4,248 to 6,496
Launch 2%
CAD 4,248 to 6,496
Production 10.8%
CAD 22,939.20 to 35,078.40
Holdback, 30 days after launch (10%)
CAD 21,240 to 32,480

// questions

Questions we get about this.

Can a literature assistant read our internal reports without them leaving our control?

Yes. The model and the search index run on servers set up for you, in the region you choose.

Which open-source models do you use for research assistants?

We choose with you, based on your documents and questions, and test a few before we pick one. You can change models later.

Can the assistant tell our scientists when a paper contradicts our results?

It can find and quote passages that bear on a question. Judging what they mean stays with your scientists.

// next

Not quite your project?

Tell us what you have in mind. We will come back to you with a range and the questions that would narrow it. Or book a call and talk it through.

Literature and research assistants on private models for biotech teams | Atheron Network Labs