Autonomous software development, under your control.
Give Ikidna an outcome. Its control plane researches the work, builds a dependency-aware plan, and coordinates specialized agents through implementation and review. Your policies decide where agents run, what they can access, and when a human steps in.
The hard part is turning agents into a delivery system.
Running one coding agent is easy. Coordinating many agents against a real product is not. Your team must translate outcomes into work, sequence dependencies, isolate execution, enforce policy, review changes, and preserve evidence.
Without a control plane, those responsibilities become another internal platform to design, integrate, secure, test, and maintain. That delays the payoff from AI and diverts engineering capacity into orchestration infrastructure.
coordinate
Turn outcomes into executable work
Research the request, populate the backlog, map dependencies, and expose the work that can run safely in parallel.
govern
Scale autonomy without losing control
Give every agent an identity, route it into the right work pool, and apply isolation, approval, and tool policies before execution.
compound
Make every run improve the next
Preserve artifacts, evidence, and feedback as product knowledge so future agents start with current context and provenance.
Purpose
Ikidna gives engineering organizations access to autonomous delivery infrastructure without requiring them to spend months becoming AI platform builders first.
Ikidna converts intent into a reviewable work graph, then executes the eligible work through policy-bound agents.
01 / define
Start with the outcome
Describe what the product or feature must achieve. Ikidna turns that prompt into an ultimate goal with measurable outcomes.
02 / research
Research the path
Research agents gather the context, product knowledge, and constraints needed to create reviewable research artifacts.
03 / plan
Build the work graph
The system creates tickets, maps their dependencies, and topologically sorts them to expose safe parallel work.
04 / orchestrate
Provision the right agents
Policies select agent identities, harnesses, work pools, network access, and isolation for every task.
05 / deliver
Implement and review
Engineering and adversarial review agents execute the work, preserve provenance, and raise pull requests against the relevant repositories.
06 / learn
Continue from feedback
Merges, review changes, and external webhooks update the plan, knowledge, and next eligible batch of work.
Adopt it your way
Start autonomous. Or earn autonomy incrementally.
Ikidna can own a bounded delivery flow or join an existing team as an AI contributor. The operating model is yours to set.
01
Greenfield autonomy
Start with a product outcome and let Ikidna research, plan, and implement the work. Feedback from tickets, reviews, and knowledge sources keeps the product moving.
Outcome-led planning
Parallel implementation
Continuous feedback loops
02
Brownfield collaboration
Bring an existing repository and backlog. Ikidna maps the work, begins with safe tasks, and contributes alongside your current engineering process.
Existing backlog intake
Human checkpoints
Incremental rollout
The dark factory pattern
Autonomy where the boundaries are known.
A software dark factory accepts an outcome, autonomously determines the work, and produces the relevant output with minimal routine oversight. Ikidna is designed to move toward that model without pretending every decision can already be automated.
Known boundsRun autonomously
Policy boundaryRequest approval
Unknown boundsEscalate to a human
Day Two Operations
Autonomy has to survive beyond the happy path.
Agent systems fail in ways ordinary pipelines do not. Models time out, tools return partial results, permissions change, context becomes stale, and generated artifacts can disagree.
If recovery, evaluation, and knowledge maintenance are not part of the architecture from day one, autonomous delivery eventually becomes manual incident handling. Ikidna treats operations as part of the delivery lifecycle, not an add-on after launch.
observe
Trace every run
Follow goals, agent identities, tool calls, artifacts, and failures across the full workflow. Route telemetry into systems such as Langfuse or Sentry without losing Ikidna's provenance.
recover
Retry with state and policy
Preserve the work already completed, classify the failure, and decide whether to retry, re-plan, or escalate. Recovery follows policy instead of restarting an opaque agent loop.
evaluate
Evaluate outcomes continuously
Run evaluations against the expected outcome, implementation, tests, and review evidence. Use the results to stop unsafe work and improve how future tasks are routed.
reorient
Keep context current
Continuously ingest feedback and evidence, supersede stale knowledge, and retain provenance. Agents begin the next run with the current product state instead of yesterday's assumptions.
01Detect signal02Trace and classify03Retry, re-plan, or escalate04Ingest what changed
Designed in from day one.Failure state, evidence, and feedback use the same orchestration and provenance model as the successful path.
Modular by design
Keep the control plane. Bring your systems.
Adopt the defaults to start quickly, then replace components where your governance, infrastructure, or operating model demands it.
core
Ikidna control plane
Work-pool orchestration
Policy enforcement
Approval routing
replaceable
Defaults with adapters
Agent runtime
Ticketing
Model harnesses
integrated
Your existing systems
Knowledge
Source control
Observability
Communications
Deployment and control
Single tenant from the first pod.
Keep Ikidna and its data inside your Kubernetes environment, or use a Kiberon-managed single-tenant deployment. Model inference remains yours. Ikidna does not bundle a model provider.
Self-hosted KubernetesOperate inside your environment and disable external telemetry.
Managed single tenantKiberon manages the deployment and uses telemetry for technical assistance.
control boundaries
Built for governed agent execution
Network isolationEach customer receives a fully single-tenant environment.
Per-run identityEvery invoked agent receives an identity for audit and provenance.
Protected dataSecrets are encrypted at rest. Databases support encryption and RLS.
Configurable sandboxesAgent isolation follows the customer's execution policy.
Integration surface
Connect the tools your team already trusts.
Ikidna coordinates the delivery system. It does not force you to replace every system around it.
Source control
GitHub · GitLab
Communications
Slack · Microsoft Teams
Observability
Langfuse · Sentry
Agent harnesses
Codex · Claude · OpenCode · Pi
Knowledge
Customer knowledge bases through MCP
Policy
Native policy engine · OPA planned
Paid private alpha
Put Ikidna to work on your delivery system.
Alpha customers receive hands-on technical assistance to get the most from the platform. Optional forward-deployed engineers can help integrate Ikidna with your repositories, policies, and existing systems.
