Legal

Responsible AI Statement

Effective date: March 1, 2026

Our Position

FlockSoft builds agentic AI systems — software that reasons, plans, and executes autonomously on behalf of businesses and their customers. We believe this technology represents one of the most consequential developments in the history of software, and we take that consequence seriously.

Responsible AI is not a compliance exercise for us. It is a product requirement, an engineering constraint, and a business imperative. The organizations that trust us to run autonomous systems inside their operations need to know those systems behave predictably, transparently, and within well-defined boundaries. That trust is our most important asset — and we protect it by building AI that earns it.

This statement describes the principles that govern how we design, build, deploy, monitor, and govern our AI systems. These are not aspirations — they are requirements that every FlockSoft product and service must meet before it reaches a customer.

Core Principles

Six commitments we
make to every client.

01

Human Oversight

Every agent we build operates within boundaries defined by human operators. We design for override, not replacement. Critical decisions — those with significant financial, legal, health, or safety implications — require human confirmation before execution.

02

Transparency

Our agents do not impersonate humans. They identify themselves as AI systems when interacting with people. We maintain full audit trails of every agent action, making the reasoning behind automated decisions accessible and reviewable.

03

Fairness and Non-Discrimination

We actively test our systems for bias before deployment and on an ongoing basis. No FlockSoft agent may be configured to make decisions based on protected characteristics — race, gender, age, religion, national origin, disability, or sexual orientation.

04

Data Minimization

Our agents access only the data necessary to complete assigned tasks. We apply the principle of least privilege to all data access. Customer data is never used to train shared models without explicit written consent.

05

Security by Design

Security is not a feature added to our AI systems — it is the foundation they are built on. Every agent includes adversarial input filtering, output validation, rate limiting, and anomaly detection to prevent misuse.

06

Accountability

FlockSoft accepts responsibility for the systems we build. We maintain incident response protocols for AI-related failures. We publish our governance practices and invite external scrutiny. Accountability is not optional — it is operational.

Hard Limits

What we will
never build.

×Systems designed to deceive or manipulate people without their knowledge
×Autonomous weapons, surveillance tools, or systems used for population control
×Systems that generate disinformation, non-consensual synthetic media, or illegal content
×Tools designed to circumvent legal protections, democratic processes, or individual rights
×Systems that make high-stakes decisions without meaningful human oversight
×AI trained on data obtained without appropriate consent
Active Commitments

What we actively
do differently.

+Red-team every agent before production deployment to identify failure modes
+Maintain a model card for every AI system that describes its capabilities, limitations, and known risks
+Provide clients with full audit logs of every agent action, accessible in real time
+Conduct bias and fairness assessments before deploying models in hiring, lending, or healthcare contexts
+Review and update our AI governance practices at least quarterly
+Publish this statement publicly and update it as our capabilities and understanding evolve
Governance

FlockSoft maintains an internal AI Review Board responsible for evaluating new use cases, reviewing incidents, and updating our governance policies. The Board meets monthly and reports to company leadership.

New agent types and significant model changes must pass a pre-deployment review that includes capability assessment, risk analysis, bias testing, security review, and documentation of known limitations. This process applies to both internal products and client-facing implementations.

Incidents involving AI-generated harm or unexpected behavior are tracked in our incident management system. We conduct post-mortems for all significant incidents and share learnings with affected clients. We are committed to improving our systems based on real-world performance, not just theoretical safety analysis.

We welcome external engagement on responsible AI. If you have concerns about how one of our systems is behaving, please contact us at the address below. We take all reports seriously.

Questions & Concerns

Talk to us
about AI safety.

If you have questions about our responsible AI practices, concerns about how one of our systems is behaving, or want to engage with us on AI safety research, please reach out. We take all communications on this topic seriously.