Kaiva lets you compose multi-step agentic workflows across your stack, run them under typed guardrails, and tie every autonomous action to a booked business outcome — with attribution, audit, and reversibility.
Every Kaiva agent moves through four stages — composed, run, attributed, audited. The same loop powers a sales nudge, a support triage, an invoice settlement, or a compliance review. Press play, or click a stage to jump in.
Every Kaiva agent is an explicit graph: triggers, tools, model calls, guardrails, and outcomes. No hidden prompts, no orchestration black box. Edit a node, and the typed contract under it updates with you.
Kaiva runs the workflow under a typed policy. The agent reasons, picks tools, and acts within its budget. Every step is observable: planner thoughts, tool I/O, guardrail checks, retries.
Every action lands on a metric your CFO already tracks. Kaiva attributes the lift via synthetic-control holdouts, not before-and-after wishful thinking, and pays the agent only for the difference.
Inputs, tool calls, model decisions, guardrail results, reviewer signatures — all on one append-only line. Exportable as a signed audit pack. Reversible until the window closes.
Agents don't succeed by running. They succeed by moving a number your CFO cares about. Kaiva ties every run to an outcome — with holdout, attribution, and a reversibility window.
Kaiva builds a counterfactual from a held-out cohort, then attributes the difference back to the agent and tool that drove it. No correlation theatre.
Three things that separate a governed agent from a prototype: how it connects, how it's guarded, and how it's proved. Kaiva brings them together.
Connectors for the systems that run the business — Salesforce, HubSpot, Zendesk, Slack, GitHub today; Stripe, SAP, Snowflake, Workday, ServiceNow shipping under MCP; plus generic SQL, SFTP, and anything behind an OAuth wall.
Build agents as composable workflows: plan, tool-call, approve, retry, branch. Kaiva handles memory, state, and escalation so you can focus on what the agent should accomplish.
Every run produces a receipt: inputs, tool calls, model decisions, policy checks, reviewer signatures. Every outcome booking is reversible and evidence-linked.
Four weeks from kickoff to a governed agent in the wild. No professional services crater, no integration theatre — just the system doing the work.
Every outcome comes with a receipt both operator and reviewer can read. Audit trail, role-based access, approval queue, and a guardrail engine — built in, not bolted on.
Inputs, tool calls, model decisions, policy checks, reviewer actions. Tenant-scoped, exportable, and indexed for search. No more reconstructing the story from logs.
Six roles by default; per-agent, per-outcome, per-connector overrides on top.
Batch-approve low-stakes, demand sign-off on high-stakes. SLA clocks, median review time, and policy-driven routing.
Declare what's true, what's bounded, and what's forbidden. Kaiva compiles your policies into typed contracts, then blocks runs that would break them — before they ship.
One console. Policy, simulated run, reversible receipt. Your risk team sees the whole thread — from the rule on the left to the money on the right — in fewer clicks than approving an expense report.
Five fields. No YAML marathon, no policy engine PhD. Kaiva compiles your declaration into typed contracts that every subsequent run is checked against.
Kaiva replays the proposed policy against real historical runs and surfaces where a guardrail would have fired, how much margin it leaves, and what the honest lift looks like.
Every run posts to the ledger with its inputs, model choices, guardrail results, and the outcome it booked against. Reversible for 30 days by default. Exportable as a signed audit pack.
One path. Starts with a conversation, ends at the same ledger.
For regulated teams running production agents across multiple outcomes, with SLAs, SSO, custom guardrails and dedicated support.
Kaiva is model-agnostic. The platform routes today between Anthropic and OpenAI; Google, xAI, open-weight models, custom fine-tunes, and customer-hosted endpoints are on the near-term roadmap. BYOK on every provider, governed through a single policy plane. Agents can be configured to select per task by capability, latency, or cost.
Your data never trains foundation models — Kaiva uses commercial model APIs under no-training terms. Every agent action lands in an append-only audit log with role-based access control. Tenant isolation, configurable retention, and PII policies are part of the Enterprise engagement. Built GDPR-native and EU AI Act-aware from day one.
A chatbot responds to prompts. A Kaiva agent plans multi-step workflows, uses enterprise tools, and executes work within bounded autonomy — with human-in-the-loop checkpoints at the decisions that matter.
A governed pilot agent typically reaches production in the first few sprints. Kaiva starts every engagement read-only — the agent proposes actions a human signs off on, so the team builds trust before autonomy is dialled up.
Yes. Kaiva was purpose-built for high-compliance environments. Every agent action carries auditable logic, bounded autonomy constraints, and an exportable audit pack suitable for regulatory review.
Outcome-based. Kaiva is priced against the business metric each agent is responsible for — no per-seat, no platform fee. Every engagement begins with a scoping call to agree the workflow and the success metric.
We keep a small group — usually 5–15% of accounts, tickets, or transactions — off the agent as a control. The difference between that group and the one the agent works on is what we bill against. You agree the baseline and the measurement rules with us before we go live, so there's no arguing about the number later.
We'll stand up a single outcome with your data, your stack, your guardrails — and walk away with a receipt, not a deck.