See where your teams get stuck with AI, and cut the waste.

Moonford anonymously analyses your AI conversations, securely inside your environment. It shows where AI work fails, what it costs and what to fix first. Conversation content never leaves your organisation.

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The licences are bought. Now the board wants the cost under control.

Most AI rollouts stall quietly. Usage drops after launch, the spend stays the same and nobody can say exactly why.

72% of IT leaders say employees struggle to fit Copilot into their daily routines.
57% say engagement declines quickly after rollout.
3% say Copilot has delivered significant value.

Source: Gartner, Digital Workplace GenAI survey of 132 IT leaders, 2024.

The answer is already written down.

Every time someone gets stuck, they say so to the assistant. It cannot find the contract. The export fails. The policy it quotes is out of date. Thousands of these moments happen every week, and almost none of them reach a ticket queue.

We analyse friction in your AI layer.

Moonford looks only at friction that affects your AI rollout: your assistants, their connections to your tools, and your agents. Each finding names the team that can fix it.

Connections

Connectors that time out, return errors or come back empty, and sources the assistant only partly reaches.

Fixed by: your platform team

Access

Licences not assigned, missing permissions, connectors not enabled for a team, and repeated sign-in prompts.

Fixed by: IT and identity

Tools behind the assistant

Data in your tools that the assistant cannot use: empty fields, duplicate records, answers that take several steps.

Fixed by: the application owner

Agents

Agents that retry in loops, stop at their step limit, pick the wrong tool or send malformed requests.

Fixed by: the agent’s owner

Coverage

Requests no connected tool can serve, and connectors that exist but go unused.

Fixed by: your AI team

Spend

More model than the task needs, tokens spent on retries, and the same question answered again across teams.

Fixed by: your AI team

Friction in tools your AI assistants and agents never touch is out of scope.

A second lever on AI spend.

Controlling AI spend usually means cutting: fewer seats, tighter token limits, cheaper models. Moonford adds a second lever: find the usage that produces nothing and remove its cause. Every fix is attributable, with a named failure, an owner, a before and an after. That gives you a record of active cost control, built on evidence from your own environment.

Where work stalls

Every recurring point where people give up, work around the assistant or escalate to a colleague, by team and by tool.
What it costs

Hours and money lost, in figures your finance team can sign off.
What to fix first

A ranked list of fixes, starting with the one that gets the most people working again.

410 people in sales could not reach the contract archive from Copilot last month. 290 hours lost. The fix: one connector permission.

Illustrative example.

Your data stays where it is.

Moonford anonymously analyses conversations, securely inside your own environment. It reports on AI, tools and work, never on individual people.

Where it runs: Inside your environment, on infrastructure you control.
What it analyses: Only the AI conversation history you choose to connect, anonymously and inside your environment.
What you see: Findings by tool, team and cost. No person is named, scored or ranked.
What leaves: With your approval, grouped figures such as rates and counts. Never conversation content.
Our access: Named, logged and revocable, for the period you agree.

Built to work with your AI stack, not to replace it.

Observability tools and AI gateways show how your AI runs. Moonford shows where AI work fails, why, and who can fix it.

	AI observability tools	AI gateways	Moonford
Built for	Engineers debugging AI apps they build	Platform teams controlling access, routing and spend per model	The AI rollout owner deciding what to fix first
What it sees	Traces, latency, errors and tokens per call	Every request routed through it: model, tokens, cost and policy	What happens in the conversation, analysed anonymously inside your environment: where AI work failed and which tool or connector caused it
Vendor assistants such as Copilot	Only apps you instrument yourself	Only traffic routed through the gateway	Yes, from exported conversation history, analysed anonymously inside your environment
Failures with no error	Partly, if someone inspects the trace	No: the call succeeded	Yes: the empty answer, the rephrase, the workaround
Cost view	Tokens per call	Spend per model, team and key, with budgets and limits	Cost of failed AI work, by cause and owner
Output	Dashboards and traces	Routing rules, limits and logs	A ranked list of fixes, each with an owner

Already run one of these? Moonford can use its logs as a further source.

A ford is the shallow point where a river can be crossed. Moonlight is what shows you the way at night. Every AI rollout has places where people cannot get across. We show you where they are.

Find the waste in your AI rollout.

We are opening a small number of early partnerships with enterprises rolling out AI assistants at scale.