Authentise Targets Technical Data Package Bottleneck with AI-Driven Workflow Tool at AMAA 2026

At the Additive Manufacturing for Aerospace and Defense (AMAA) 2026 conference, Authentise unveiled a new AI-driven workflow tool designed to automate the creation and management of Technical Data Packages (TDPs) for additive manufacturing. The software, integrated into Authentise's existing digital thread platform, uses machine learning to extract, validate, and structure engineering data from CAD models, build files, and inspection reports into a standardized TDP format. CEO Andre Wegner demonstrated the tool's ability to reduce manual data assembly time by over 70% during qualification workflows, directly addressing a pain point that has slowed AM adoption in regulated industries. The announcement comes as Authentise continues to expand its software-as-a-service (SaaS) footprint across aerospace and defense supply chains.

This move targets a persistent bottleneck in the AM value chain: the cost and complexity of generating compliant technical data packages for qualified production. While much of the industry's software innovation has focused on design optimization, simulation, or machine monitoring, the administrative overhead of documentation for regulated parts remains a largely manual, error-prone process. Authentise's tool directly competes with in-house PLM workarounds and niche document automation solutions from companies like Oqton and Link3D, but differentiates by embedding AI directly into the TDP creation step rather than treating it as a downstream export. For aerospace and defense primes, where every part requires a traceable data package tied to a specific material lot, machine parameter set, and inspection record, automating this step could meaningfully reduce the non-recurring engineering cost of qualifying a new AM part. The tool also aligns with the broader push toward digital thread continuity, a concept that has gained regulatory traction as the FAA and DoD increasingly mandate born-digital certification artifacts.

From a practical standpoint, Authentise must now demonstrate that its AI can handle the variability of real-world TDP requirements across different primes and programs, each with their own data schemas and acceptance criteria. The tool's value will be measured not by demo speed but by its ability to pass an audit without human rework. For buyers in aerospace and defense, this is a concrete step toward reducing the qualification overhead that has kept AM from scaling beyond low-risk, non-critical parts. The company's next milestone will be securing a pilot deployment with a major prime or tier-one supplier to validate the tool against production-grade documentation standards.