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Brightly AI calibrates a restoration model to each facility's own microscope so live-cell and cleared-tissue imaging can run at 2.5-12% of normal exposure. Restored volumes carry per-voxel confidence and pass a validation gate before delivery.
PLAYA DEL REY, Calif. - Californer -- Brightly AI, https://brightly-ai.org , a computational imaging company, today launched its restoration platform for fluorescence microscopy. The platform trains an Instrument Twin, a restoration model calibrated to one physical microscope, and uses it to recover quantification-grade volumes from acquisitions made at 2.5-12% of normal light exposure. The launch addresses the photon budget: the constraint forcing researchers to choose between noisy data and samples damaged by phototoxicity and photobleaching. Unlike generic denoising tools, every output ships with a per-voxel Confidence Map and a pass/block verdict from a validation gate.
The platform runs a six-stage pipeline. A facility first performs Dose-Pair Capture, a guided 45-minute protocol that acquires paired low-dose and reference exposures on its own instrument. On bare-metal GPU clusters, Brightly AI fine-tunes a 3D residual restoration network to that exact optical configuration, a training job that holds roughly 200 GB of paired image patches in memory across a multi-hour convergence. In production, volumes are restored by tiled ensemble inference: five stochastic passes over as much as 300 gigavoxels per channel, with the variance across passes producing the Confidence Map. A Fidelity Gate then scores each volume against held-out pairs and blocks anything outside the instrument's calibrated error envelope. Drift Watch monitors noise statistics and point-spread-function shape continuously, triggering recalibration before quality degrades.
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Computational restoration software for research fluorescence microscopy is an estimated $250-300 million annual market, based on published light-microscopy market figures of $2.5-3.5 billion with a 12-15% software attach rate, a figure Brightly AI triangulated within 10% by an independent bottom-up count of roughly 24,000 restoration-relevant instruments in active research service. The immediate problem is operational: imaging cores bill $50-150 per instrument-hour, and failed longitudinal experiments burn both budget and scarce booking slots.
Brightly AI, https://brightly-ai.org, is live with 12 Instrument Twins across five design-partner facilities, with fleet medians of 16.8× dose reduction and +8 dB restoration gain. The company raised a $250,000 pre-seed round in June 2026. Over the next 12 months, Brightly AI plans to publish a versioned public fidelity benchmark across modalities and expand its design-partner cohort.
The platform runs a six-stage pipeline. A facility first performs Dose-Pair Capture, a guided 45-minute protocol that acquires paired low-dose and reference exposures on its own instrument. On bare-metal GPU clusters, Brightly AI fine-tunes a 3D residual restoration network to that exact optical configuration, a training job that holds roughly 200 GB of paired image patches in memory across a multi-hour convergence. In production, volumes are restored by tiled ensemble inference: five stochastic passes over as much as 300 gigavoxels per channel, with the variance across passes producing the Confidence Map. A Fidelity Gate then scores each volume against held-out pairs and blocks anything outside the instrument's calibrated error envelope. Drift Watch monitors noise statistics and point-spread-function shape continuously, triggering recalibration before quality degrades.
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Computational restoration software for research fluorescence microscopy is an estimated $250-300 million annual market, based on published light-microscopy market figures of $2.5-3.5 billion with a 12-15% software attach rate, a figure Brightly AI triangulated within 10% by an independent bottom-up count of roughly 24,000 restoration-relevant instruments in active research service. The immediate problem is operational: imaging cores bill $50-150 per instrument-hour, and failed longitudinal experiments burn both budget and scarce booking slots.
Brightly AI, https://brightly-ai.org, is live with 12 Instrument Twins across five design-partner facilities, with fleet medians of 16.8× dose reduction and +8 dB restoration gain. The company raised a $250,000 pre-seed round in June 2026. Over the next 12 months, Brightly AI plans to publish a versioned public fidelity benchmark across modalities and expand its design-partner cohort.
Source: Brightly AI
Filed Under: Artificial Intelligence
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