Who the assessment is for
The readiness assessment is for companies that want to adopt AI agents seriously — not as an isolated experiment, but as a capability that must run with governance. It is especially useful for those who have already tried a pilot and stalled on context quality, or who want to avoid that mistake.
If your question is "are we ready to put agents into production, and which processes do we start with?", this is the starting point. You leave with a clear picture of the situation and a prioritized path.
Symptoms of low readiness
A few signs indicate the company is not yet ready to scale agents — and that an assessment will save time and money:
- Scattered knowledge. Critical information lives in drives, wikis, emails and people’s heads, with no single trusted source.
- Pilots that do not scale. Proofs of concept work in the demo and break with real data and permissions.
- Inconsistent permissions. No one is sure who can see what — which makes agents risky.
- Unreliable answers. When tested, the agent errs, mixes sources or invents, and there is no way to audit it.
- No context owner. There is no clarity on who governs the sources and keeps the knowledge up to date.
What we assess
The assessment covers the dimensions that actually determine whether agents will work in your company: the knowledge sources and their state, the candidate processes, the permission and privacy risks, the context gaps and the required architecture.
The assessment is practical and decision-oriented — not a theoretical report. The goal is to leave with clarity on where to start and what needs to be prepared first.
What you receive
The assessment ends with concrete deliverables that guide both the decision and the execution:
Process map
Candidate processes for agents, with impact potential and complexity.
Source inventory
Where knowledge lives, in what state and what needs to be prepared.
Permission risks
Where scope is ambiguous and could cause leakage or exposure.
Knowledge gaps
Topics that lack a trusted source to support answers.
Prioritization
A recommended sequence of use cases, from highest return to lowest risk.
Recommended architecture
How to organize context, governance and delivery for the chosen use cases.
Suggested technology
An agent-technology recommendation for each case — Claude, OpenAI Agents, LangGraph or another — without lock-in.
Pilot plan
Scope, metrics and steps for the first use case to enter production with governance.
Examples of assessed processes
Candidate processes vary by industry, but a few come up often because they combine high volume with documentable knowledge:
- Internal support: Answering employee questions about policies, systems and processes.
- Customer service: First-level answers based on a controlled knowledge base.
- Sales enablement: Querying product materials, pricing and proposals with up-to-date sources.
- Operations and procedures: Guidance on internal flows from official documentation.
How the assessment becomes a pilot
The assessment does not end in a PDF. The central deliverable is a pilot plan: a prioritized use case, with clear scope, prepared sources, defined governance and agreed success metrics. From there, implementation starts with controlled risk and measurable value.
Because the context layer is independent of the runtime, the pilot does not tie the company to a vendor: the governed base built there serves any runtime in the future.
Frequently asked questions
How long does the assessment take?
It depends on the scope and the number of sources and processes involved, but it is designed to be fast and objective — weeks, not months — because the focus is decision and pilot plan, not an exhaustive study.
Do I need to have already chosen a runtime?
No. Part of the assessment is precisely to recommend the most suitable runtime for each case. Because Chatydata governs context independently of the runtime, you are not locked into a premature choice.
Is the assessment useful if I already have a pilot running?
Yes. It is common to arrive here after a pilot that stalled. In that case, the assessment identifies why it does not scale — usually context and permissions — and what to prepare to unblock it.
What happens after the assessment?
You are left with a prioritized pilot plan and the recommended architecture. Implementation is optional and follows what the assessment points to, starting with the highest-return, lowest-risk use case.
Is this a disguised software sale?
The assessment has value on its own: you leave with a source map, risks and a plan, regardless of whether you continue with Chatydata. The tool recommendation is a consequence, not a prerequisite.
Free, no-commitment assessment: you leave with a source map, risks and a pilot plan.
Assess whether your company is ready to operate AI agents