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XAI: A Full AI Pipeline.
AI You Can Trust.
From Design to Run-time Deployment. 

The Problem We Solve

Enterprises want AI—but in aviation, telecom, defense, and other high-stakes environments, “black-box” AI won’t fly. Teams need systems that are auditable, certifiable, and explainable from day one.

Our Answer

Humanitas delivers a full, certifiable, and explainable AI pipeline that carries your project from mission definition to real-world deployment—with the evidence regulators and enterprise risk teams require.

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01

Design Phase

  • Mission definition & planning: Start with clear objectives, environment, and constraints.

  • Simulation-first approach: Test drones, networks, RF signals, and even cyberattacks through digital twins before field trials.

  • Data with integrity: Blend real-world sensor/telecom data with synthetic data generated from advanced simulators, ensuring fairness and coverage.

02

Build & Test Phase

  • Model development: Advanced training techniques (transfer learning, reinforcement learning, federated learning) combined with hardware-aware optimization (quantization, pruning, FPGA acceleration).

  • Evaluation & verification: Robustness testing against edge cases, noise, and adversarial scenarios.

  • Explainability integration: Explainability built-in plus post-hoc interpretability, verified through human-in-the-loop evaluations.

  • Certification-ready evidence: Formal assurance cases, safety arguments, and traceability matrices aligned with DO-178C and ISO/IEC standards.

03

Runtime Phase

  • Deployment on accelerated hardware: FPGA, SDR, and GPU clusters ensure high-performance and low-latency AI in the field.

  • Continuous assurance: Drift detection, retraining triggers, and safe rollback mechanisms ensure long-term trustworthiness.

  • Monitoring & orchestration: Real-time dashboards for performance, health, and compliance, with automatic recertification triggers when significant changes occur.

The Full AI Pipeline

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01

Define scope & requirements

Translate stakeholder needs into certifiable AI requirements.

02

Performance assessment

Set measurable KPIs, reliability benchmarks, and failure modes.

03

Validation & testing

Validate data, scenarios, and AI models under expected conditions.

04

Explainability & bias checks

Demonstrate fairness, transparency, and coverage of decision paths.

05

Formal verification & assurance

Build structured safety cases using GSN (Goal Structuring Notation).

06

Software quality & configuration

Secure coding, strict version control, and audit logs.

07

Continuous monitoring

Drift detection, retraining, and anomaly tracking in real-world use.

08

Certification package generation

Compile audit-ready reports and evidence for regulators.

Certification Pipeline:
Turning AI into Trustworthy AI

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01

Requirement phase

Define mission goals, predictive maintenance parameters, and planning.

02

Design phase

Data engineering, cleaning, transformation, and feature exploration.

03

Coding phase

Model development, optimization, simulation, and explainability checks.

04

Integration phase

Deployment, orchestration, monitoring, and retraining triggers.

Lifecycle Phases: From Idea to Deployment

Ensures traceability and accountability from the first requirement to the last field deployment

01

Aircraft Maintenance

Aerospace & Defense – Assured Autonomy

Trusted AI for aviation and defense requires certifiable autonomy. XAI ensures drones, aircraft, and mission systems operate with full transparency, compliance, and safety assurance.

02

Dish Antenna

Telecom – Explainable Connectivity

Telecom providers depend on reliable networks. XAI enables smarter management of 5G, RF, and satellite systems, optimizing spectrum, routing, and uptime with explainable, edge-ready intelligence.

03

Aerial View of Containers

Logistics & Supply Chain – Transparent Logistics

From global shipping to last-mile delivery, logistics relies on precision and efficiency. XAI powers transparent, accountable decision-making across fleets, warehouses, and supply chains—improving performance while meeting regulatory standards.

04

Form and stethoscope

Regulated Enterprises – Responsible Enterprise AI

In highly regulated sectors like finance, insurance, and healthcare, AI adoption must be responsible and audit-ready. XAI provides the traceability, explainability, and compliance needed to innovate with confidence.

Real-World Applications

XAI for a wide range of vertical industries and use cases

Why It Matters

When AI powers critical decisions, trust is everything.

Humanitas AI provides not just performance, but also transparency, compliance, and certification-ready assurance.

01

Certification-first design

Built to align with DO-178C/DO-330 and modern AI governance (ISO/IEC 42001, NIST AI RMF, IEEE 7001/7003)—not retrofitted later.

02

Explainable by default

Every decision is linked to data, tests, and reports—no black boxes.

03

Proven multi-layer platform

We integrate simulation & digital twins, swarming, and telecom/edge orchestration into one flow for mission-ready operations.

04

Market momentum

Partnerships with aerospace research centers and early deployments in telecom and swarm simulations.

Why Humanitas XAI?

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