Use cases

Four ways teams put Quordo to work: FinOps for AI spend, agent coordination, multi-provider governance, and an audit trail for cost and agents.

FinOps for AI and LLM spend

Turn opaque provider invoices into per-team accountability. Attribute every dollar across all five providers, set budgets that alert before they blow, and export clean numbers for chargeback.

For: Finance, FinOps, and platform leads accountable for the AI bill

The problem

A single OpenAI or Anthropic invoice tells you what the organization spent — not who spent it. Spend is scattered across providers, projects, and keys, the bill arrives a month late, and finance has a number to pay rather than a number to manage.

How Quordo solves it

  1. Connect every provider Add your OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, and Google Vertex connections. Credentials are encrypted at rest and never exposed back to the UI.
  2. Attribute usage to teams Assign each connection to a team. Quordo stamps every usage event with that team and stores provider, model, and cost on the event, so the dashboard slices spend by team, model, and provider — across OpenAI, Anthropic, Azure OpenAI, Bedrock, and Vertex.
  3. Set budgets and alerts Set a monthly limit org-wide or per team. Deduplicated threshold alerts warn you at near-limit and escalate at over, and anomaly detection flags spend spikes before the bill lands.
  4. Export for chargeback Export attributed spend to CSV and push AI cost back to the cost centers that incurred it — no re-deriving the numbers by hand.

Outcomes

  • Every dollar of AI spend has a team's name on it.
  • Overruns and anomalies surface before the invoice, not after.
  • Chargeback and showback run on numbers finance can trust.

Coordinate a fleet of AI agents

Give your agents a shared, versioned source of truth, handoffs with context, and an auditable trace — so a swarm of agents behaves like one accountable team instead of three private notions of the truth.

For: Platform engineering leads running a growing fleet of agents

The problem

Today's agents scale one person's output, but the coordination between them is still done by humans — handoffs in Slack, alignment in standups. Each agent keeps its own context, work forks, and when something goes wrong there's no shared record of what happened.

How Quordo solves it

  1. Register your agents Any agent that speaks MCP — Claude Code, Devin, Cursor, and others — joins a mission via Quordo's MCP server, and agents that speak Google's A2A protocol join over Quordo's A2A JSON-RPC endpoint. No bespoke glue.
  2. Share one source of truth Each mission has versioned context that every agent reads and writes, so they operate on the same facts instead of drifting apart.
  3. Hand off with context Agents hand work off with the mission context attached, so the next agent continues the work rather than rediscovering the state.
  4. Watch coherence and resolve conflicts Coherence % rolls up shared-context agreement across the mission. When two agents write the same fact, optimistic-concurrency conflict detection flags it so a human resolves it before the work breaks.

Outcomes

  • One number — coherence % — tells you whether the swarm is aligned.
  • Handoffs carry context, so agents continue instead of restarting.
  • Humans stay at the top of the loop, intervening only on conflicts.

Govern a multi-provider AI estate

Every team buys its own AI tools and runs its own agents. Quordo gives you one plane across all five providers and any MCP agent — one login, one cost model, one audit log — without forcing everyone onto a single vendor.

For: CIOs and Chief AI Officers standardizing AI across the org

The problem

AI is fragmenting your company. Spend and work are scattered across providers, invoices, and machines, each team makes its own choices, and there's no shared truth, no per-team attribution, and no audit trail of who did what.

How Quordo solves it

  1. Bring the whole estate onto one plane Connect OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, and Google Vertex on the Spend surface, and register any MCP agent on the Coordinate surface — without standardizing everyone onto one vendor.
  2. Standardize attribution and policy Map connections to teams once and govern budgets, alerts, and access from a single cockpit, so policy is consistent even when the underlying tools aren't.
  3. Reconcile cost and coordination Because both surfaces share one data model, per-run cost reconciles into per-mission and per-team spend — one question, one answer, across every provider and agent.

Outcomes

  • One control plane across five providers and any MCP agent.
  • Consistent attribution and governance without vendor lock-in.
  • A single source of truth instead of N invoices and N standups.

An audit trail for AI cost and agents

When the bill lands or an agent goes wrong, you need a record. Quordo keeps an append-only trace of agent activity and an audit log of every mutation, so you can reconstruct who did what — across spend and coordination.

For: Security, compliance, and platform owners who need a record

The problem

When an agent goes off the rails or a budget gets blown, there's usually no shared truth and no trail. Logs are scattered, mutable, and incomplete, and reconstructing what happened means stitching together screenshots and memory.

How Quordo solves it

  1. Record agent activity, immutably Runs, context writes, handoffs, conflicts, and resolutions land in an append-only trace. Nothing is edited or deleted, so the timeline is a record you can trust.
  2. Log every mutation Every change on the Spend surface — connecting a provider, assigning a team, setting a budget — is captured in an audit log, with threshold alerts recorded alongside.
  3. Reconstruct cost and cause together Because cost reconciles into the same model, you can answer both "what happened?" and "what did it cost?" from one place when an incident review needs both.

Outcomes

  • An immutable record of who did what, across agents and spend.
  • Faster incident reviews — the trail is already there.
  • Accountability your security and compliance stakeholders can see.