3 enterprise organisations requested programme information in the last 24 hours
AI Agents don't fail
at build time.
They fail in the
real world.
AI reliability is not a testing outcome. It is a deployment requirement.
TaskHived provides independent reliability assurance before systems reach production.
TaskHived is the independent reliability infrastructure for enterprise AI deployment.
Not a testing tool. Not a QA layer. A confirmation that reliability exists before it is required.
The Problem
AI failures are invisible in testing. They are consequential in production.
Lab testing confirms controlled performance. It does not confirm real-world reliability.
Real-world conditions expose failures that controlled evaluation is not designed to surface.
TaskHived closes that gap before deployment.
Without TaskHived
- Failures surface in production, not before
- No independent assurance record on file
- Governance exposure with no independent defence
With TaskHived
- Reliability independently confirmed before go-live
- Deployment risks identified and documented
- Governance record in place before production
Why It Matters Now
Deployment is accelerating.
Validation is not.
80% of enterprise AI projects fail to deliver intended value in production. The gap is not in build quality. It is in deployment reliability.
When they fail, the average incident costs $5.72M. The reputational consequences are not recoverable and do not appear in the initial cost estimate.
72% of S&P 500 companies disclose AI as a material risk. Independent confirmation is now a governance expectation, not an internal decision.
What TaskHived Does
Independent assurance. Before exposure.
Assess
Independent reliability assessments of AI systems. Conducted before production. Delivered as a formal record.
Identify
Surface deployment risk, behavioural failures, and reliability gaps before systems reach real-world use.
Confirm
Confirm, independently, that AI systems meet the reliability standard required for production.
Certify
Deliver a defensible, independent reliability record for governance, compliance, and executive confidence.
How TaskHived Fits
Where TaskHived Fits.
Your AI System
LLM, agent, or AI deployment
TaskHived
Independent assurance
Real-World Use
Users, decisions & consequences
TaskHived sits between AI deployment and real-world exposure. The assurance layer that governance, compliance, and risk teams require before they can sign off.
Where It Matters
Where the absence of independent validation creates the greatest exposure.
AI assistants & copilots
AI assistants operating at scale carry no margin for inconsistency. A single systemic reliability failure compounds faster than any remediation can contain it.
LLM-generated content
Content generated at scale reaches users with no independent checkpoint. Errors accumulate undetected until consequences are already incurred.
Decision-support systems
AI-informed decisions in finance, healthcare, and operations carry real consequences. In autonomous systems, those decisions happen without oversight.
Customer-facing AI
Customer-facing AI carries your enterprise reputation on every interaction. Reliability gaps are not caught internally until they have already reached your users.
The Risk
Reliability gaps testing cannot surface. Consequential when they emerge in production.
Invisible until consequential
Systems without independent assurance surface failures in the worst possible context: live production, real users. 65% of consumers stop trusting a brand after an AI incident. That trust does not return.
Irreversible consequence
AI incidents trigger an average 7.5% stock price decline within 30 days. The market records it. The organisational memory outlasts the fix.
A New Category
Not a testing tool. An independent assurance infrastructure.
Validation Network
The Specialist Assessment Network.
A closed network of domain specialists who conduct independent reliability assessments. Governed entry. Not open access.
Acceptance is determined by domain expertise and assessment track record. Not availability or volume.
Governed entry
Every specialist is accepted on the basis of domain depth, professional track record, and assessment integrity. Scale has no bearing on selection.
Confidential programme structures
All assessment activity is governed by defined programme conditions. No open access. Confidential by design.
Independence as infrastructure
Independence is not a feature of the programme. It is the programme. Without it, there is no assurance.
0%
of AI projects fail to deliver business value in production (RAND, 2025)
0%
of GenAI pilots fail to reach production or deliver ROI (MIT, 2025)
0%
average accuracy drop from lab to production deployment (Kili, 2025)
About TaskHived
Unvalidated AI is already in production. The question is who confirms it is reliable.
TaskHived delivers independent reliability assurance for AI systems operating in real-world environments. Reliability is confirmed before it is assumed, not after a failure has already occurred.
Not a testing tool. Not internal QA. An independent confirmation that reliability exists before it is required.
"AI reliability is not a testing outcome. It is a deployment requirement."
AI Deployment in the News
The regulatory environment is hardening.
Independent assurance is now a governance requirement.
TaskHived Insight
Evaluation measures performance. Validation decides whether the deployment is fit for real-world use.
Read the practical guide to AI agent evaluation versus validation, including tools, permissions, repeated trials, recovery, human authority, and the evidence needed before production.
Read the evaluation versus validation guide What is AI agent validation?Enterprise Validation Gap
The distance between apparent capability and what an organisation can responsibly prove it is ready to do.
Validation Layer
An independent checkpoint between AI capability and enterprise exposure.
Intent-Based Access Control
Keeping an agent's authority tied to purpose, intent, action, context, and time.
Frequently Asked Questions
Clear answers before you decide to deploy.
What is AI agent validation?
AI agent validation is the evidence-based determination that a complete Agentic AI deployment is fit for a specific intended use under defined conditions and consequences.
How is validation different from testing?
Testing checks specified components or behaviours. Validation adds the real deployment context, users, permissions, tools, consequences, human authority, recovery, and residual risk needed for a release decision.
What does TaskHived assess?
TaskHived assesses AI outputs and deployment behaviour, including outcome correctness, source support, tool use, permissions, uncertainty, recovery, escalation, and release evidence.
When should an enterprise validate an AI agent?
Validate before an agent reaches customers, employees, regulated decisions, sensitive data, external systems, or any action where a wrong result creates material exposure.
Request Access
Confirm your AI is reliable before it reaches the people who depend on it.
Scoped to your deployment. Independent of your vendor, your team, and your internal assumptions.
Without independent assurance
Your deployment carries no third-party reliability record. 44% of enterprises report negative AI outcomes averaging $4.4M per incident. All of it identified after the fact.
AI is already in production.
The question is whether it has been independently confirmed before it reached your users.