InFlightAI (formerly Levatas) vs Technosylva (2026): Pricing, Features & Verdict

Why choose InFlightAI (formerly Levatas)

• Has a free plan (Technosylva does not)
• Higher Customization score (8/10 vs 6/10)
• Higher Integration score (7/10 vs 6/10)

Why choose Technosylva

• Higher Analytics score (9/10 vs 8/10)
• Higher Scalability score (8/10 vs 7/10)

InFlightAI (formerly Levatas)

Pros

• About 37 ready-to-use computer vision models, including analog gauge reading (patented in 2019), thermal hotspots, corrosion and utility pole condition, so teams do not need to train models themselves.
• Deep hardware partnerships: Boston Dynamics' first Certified Technology Partner for Industrial AI, plus a native integration with Skydio Cloud and the X10 dock.
• Low-confidence detections go to human reviewers, and their feedback retrains the models on the customer's own data, which reduces false alarms over time.
• Pushes inspection results into IBM Maximo, Oracle EAM, IFS Cloud and MaintainX, and offers an API for other systems.
• Runs as containers in a private cloud, on-premises or at the edge, and the vendor says data stays inside the customer's network.

Cons

• No public pricing. Outside the 30-day trial for Skydio X10 owners, buyers have to go through sales.
• It analyzes data but does not capture it, so you need Skydio drones, Spot robots or compatible cameras.
• No native work order or CMMS module. Maintenance jobs have to be created in a connected EAM.
• Almost no independent user reviews on G2, Capterra or forums, which makes it hard to verify the vendor's performance claims.
• No published security certifications such as SOC 2 or ISO 27001 were found on the website.
• The 2026 rebrand from Levatas means older documentation and press still use the old name, and the support portal remains on a levatas.com domain.

Technosylva

Pros

• Uses about 27 years of fire data and modeling, which the CEO presents as an edge over newer venture-backed wildfire startups.
• FireSight scores individual assets by both ignition likelihood and consequence, such as acres burned and buildings destroyed, which supports WMP filings and hardening decisions.
• Gives hourly asset-level fire-risk forecasts up to five days ahead to support PSPS and crew pre-positioning decisions.
• Major utilities (PG&E, SCE, SDG&E, Xcel) and CAL FIRE use it, and CAL FIRE analysts used it during the Park Fire.
• Partnerships with AiDASH (vegetation) and Pano AI (camera detection) connect its risk models with field and sensor intelligence.

Cons

• No public pricing, and EPRI flags cost as a barrier for smaller utilities and co-ops.
• There are almost no independent user reviews on G2, Capterra or community forums, so its claims are hard to verify.
• It is a risk modeling platform, not an asset maintenance system: no work orders, inspection forms or asset registry were documented.
• No public API documentation or security attestation such as SOC 2 could be found.
• The Pano AI integration was still being validated with select customers in early 2026 before wider release.