Meet OmniBioFex 1.0 47B — a combined vision + text engine (27B vision head, 20B text head) that reads a scan and writes a structured clinical report: findings, impression, differential diagnosis, and management. Four scan modes, four languages, six templates.
Every scan is a choice. Pick the mode that matches the question you're asking. Prices are debited from your wallet per successful run — failures auto-refund.
The full report — findings with confidence, impression, advice, differential, and management. Optional 2-pass localization verification.
→ RECOMMENDED FOR ROUTINE READSTwo independent vision passes on the same image. Agreement scores per finding. Best for ambiguous studies or high-stakes reads.
→ TWO PASSES · AGREEMENT SCORESweeps the study for fractures, opacities, and lesions. Returns bounding boxes with severity colour-coding on the original image.
→ ANNOTATED BOUNDING BOXESUpload a prior and a current study. The engine returns interval changes, new findings, and resolved findings side-by-side.
→ PRIOR + CURRENT · INTERVAL REPORTA live replay of what a scan actually goes through. The beam sweeps the frame, the log streams the pipeline's real stages on a real study.
A toggle inside the app that turns the terminal into a shared-room-safe workstation. One click. Everything else in the product keeps working exactly the same.
Every scan produces a formal clinical imaging report. Structured like a radiologist's report, exportable to a multi-page PDF, with a live follow-up chat that never loses context.
Auto-detected — "CHEST X-RAY · PA View", "CT BRAIN · Axial", "MRI KNEE · Sagittal".
6–12 discrete clinical sentences. Each with confidence and a 3×3 region tag.
One-sentence diagnostic conclusion. "No abnormality detected" when normal, or the leading diagnosis otherwise.
One-line recommendation — often "clinical correlation recommended" or a specific next step.
3–6 conditions ranked most-to-least likely, each with a short rationale.
3–6 specific next steps — imaging, labs, referrals, or conservative management.
Multi-page PDF with letterhead. Markdown for docs. Raw JSON for pipelines.
Ask anything about the report — image-grounded, zoom-aware. $0.01 per turn. Saved forever.
Sign in with Google. Attach a scan. Enter the patient's name, age, gender, language, and template (all optional except the image). That's it — the pipeline does the rest in 15–40 seconds depending on mode.
One-click Google OAuth. No passwords, no email verification, no credit card. Account live the moment you consent.
Drop a chest X-ray, CT, MRI, or histopathology slide. Full image, no cropping. DICOM is converted in-browser. Client-side compression to 1600px.
Standard, Multi-model, Find, or Compare. Optionally add patient name, age, sex, language (4), and template (6).
Four sequential steps: vision extraction (27B) → impression → differential + management (20B) → final assembly.
The report appears in chat. Click EXPORT PDF for a clinical-grade document. Then ask anything — follow-up chat is live at $0.01/turn.
The chat is not a form. It is a live session. Every message is saved, every image is preserved, and follow-up questions are grounded in the original study.
Up to 2 images per request in Compare mode. Single image in all others.
Upload a .dcm file and the browser converts it to a JPEG before sending. Single-frame only.
Ask anything about the report. Image-grounded. Zoom-aware. $0.01 per turn.
PDF · Markdown · JSON — from any report, at any point in the chat.
Every session is saved. Reload the page — it's all still there.
English, Hindi, Tamil, Telugu. General, Chest, Neuro, Ortho, Cardiac, Patient-Friendly.
One toggle. Light for clinical review, dark for reading rooms.
Redacted previews and 15-min idle signout when you share the terminal.
Click any stage. Watch how a single image travels through the pipeline and becomes a structured report.
A real-time peek at what a running inference actually looks like on the backend.
Vision and reasoning are different problems. A single monolithic model is a compromise on both. So we split them.
Extracts 6–12 discrete findings with per-item confidence and 3×3 region tags. Runs a parallel fracture-hunt audit. Emits strict JSON.
Takes the structured findings, writes the one-line impression, ranks a differential diagnosis, and drafts 3–6 management steps.
Each stage calls the head that is best for it. Routing beats stacking — predictable memory, predictable cost.
Owners on the Enterprise tier can top up a single shared wallet and invite up to 10 seats. Every seat shares the same pipeline; every action is audited.
One wallet, one shared history. Owner invites by email, sets role, transfers seats between members.
Admin, Member, Technician, Reviewer, Billing — each with scoped permissions inside the team panel.
Owner tops up once; every member scans from the same balance. Every member can switch between personal and team wallet with one click.
Upload a clinic name and logo (PNG/JPEG/WebP ≤ 500 KB). It appears on every team member's PDF letterhead.
Completed reports POST as HL7 FHIR DiagnosticReport to any HTTPS endpoint. Save + send test from the team panel.
Every action is logged. Set an optional monthly USD ceiling on team-wallet spend.
One key per wallet. POST to api.omnibiofex.cloud/apiInference with Authorization: Bearer. Same model, same rate.
No subscriptions. No auto-renewal. Failed calls auto-refund. Balance never expires.
OmniBioFex 1.0 47B is a routed combination of two model heads served together on Groq's LPU stack. A 27B vision head reads the image. A 20B text head writes the report. Combined: 47B parameters — chained, not stacked.
Benchmark figures are the published numbers for the underlying vision head (qwen/qwen3.8-27b). They describe the model, not the combined pipeline.
One engine. One report format. All output is decision-support material for qualified professionals.
Lung fields, cardiac silhouette, mediastinum, pleural spaces, osseous structures.
Descriptive observations on single CT slices. The model does not reconstruct 3D volumes.
Descriptive observations on single MRI frames. Not a substitute for a radiologist's read.
Radiograph observations. Not a fracture-detection product — findings require professional review.
Tissue images. Not a pathology AI; output must be reviewed by a pathologist.
Skin lesion images. Output must be reviewed by a dermatologist before clinical use.
Free tier, or top up a wallet and skip the cooldown. No card stored. No auto-renewal.