Solunar AI / Research institutes

AI access built for research institutes

Q: Will the model be degraded and affect research conclusions?

No. We run through official API channels — no reverse-engineering, no downgrading, no model swaps — so you use the full-capability model. During onboarding we can verify authenticity against your real tasks before you go live.

Q: How do multiple research groups stay separate?

Each group or project gets its own keys and budget, with quotas and overage blocks, and usage and cost visible per group. One official endpoint, shared across groups, without interference.

Q: Is reimbursement and audit easy to handle?

Usage and billing are transparent and reconcilable — who spent what and where is clear on a single sheet, which makes reimbursement and audit straightforward.

Q: Is research data safe?

Your data is yours — never captured, sold, or used to train models, with data boundaries written into the contract and backed by an accountable, incorporated entity.

Full-capability models, spend you can account for, data you can keep safe — so AI reliably supports research workflows, without staffing an engineering team of your own. Multiple groups share one official endpoint, each with its own budget, keys, and audit trail.

Request access → What is an AI gateway

The access problems research teams face

Spend has to add up

Reimbursement and audit require accounting for every charge; a black box won't pass.

Models can't be diluted

Research conclusions depend on model quality; downgrading or swaps quietly corrupt results.

Many groups, one account

Multiple groups and projects share access and need per-group budgets, permissions, and visibility.

Data has requirements

Research data often carries confidentiality and compliance needs; boundaries must be clear.

How Solunar helps

Official channels, full-capability models, not degraded — research builds on the real model, with authenticity verified at onboarding.
Budgets and keys per group or project, with visible usage and reconcilable billing — spend on one sheet, clear for reimbursement and audit.
Data never captured, sold, or used for training, with boundaries written into the contract — compliant and under control.
Integration, validation, and delivery handled end to end — no need to staff an AI engineering team.
An incorporated entity and independent nodes — stable and traceable, dependable for the long term.

Fits these scenarios

Literature review & synthesis

Search, summarize, and synthesize large bodies of literature.

Experimental & survey data analysis

Assist with processing and interpreting structured and unstructured data.

Paper & report drafting

Draft, refine, translate, and format — with human review in the loop.

Research workflow automation

Embed models into existing pipelines and tools for everyday use.

How to get started

Access is invite-only for now. Email us about your institute or group and your use case; we'll assess and arrange onboarding — and one team owns the whole path, from integration and validation to delivery.

Request access →

FAQ

Will the model be degraded and affect research conclusions?

No. We run through official API channels — no reverse-engineering, no downgrading, no swaps — so you use the full-capability model; during onboarding we can verify authenticity against your real tasks before you go live.

How do multiple research groups stay separate?

Each group or project gets its own keys and budget, with quotas and overage blocks, and usage and cost visible per group. One official endpoint, shared across groups, without interference.

Is reimbursement and audit easy to handle?

Usage and billing are transparent and reconcilable — who spent what and where is clear on a single sheet, which makes reimbursement and audit straightforward.

Is research data safe?

Your data is yours — never captured, sold, or used to train models, with data boundaries written into the contract and backed by an accountable, incorporated entity.

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