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Home/Platform/Reasoning Engine
Platform · Reasoning & Planning

Plans that survive contact with the real world.

Chain-of-thought reasoning, decision trees, dependency graphs, and dynamic replanning — the engine behind reliable autonomous execution.

Chain-of-thoughtDecision treesDynamic replanningVerifier agents
CoT
Verified loops
Replan
On failure
Eval
Per workflow
Cost
Budget-aware
How it reasons

A structured approach to autonomy.

Six engine primitives combine to turn open goals into deterministic, explainable execution.

Goal decomposition

Convert open-ended goals into a typed task graph with inputs and dependencies.

Chain-of-thought

Step-by-step reasoning with self-critique and verifier loops.

Decision trees

Branching logic with explicit guard conditions and confidence thresholds.

Dynamic replanning

Detect failures, swap tools, retry intelligently, escalate gracefully.

Verifier agents

Independent checkers validate plans and results before commit.

Cost-aware planning

Optimize plans against latency, token cost and accuracy budgets.

How planning works

Plans that survive failure

Real enterprise workflows fail in messy ways: APIs time out, data is missing, approvers are out, policies change. The xyner reasoning engine handles all of it — fallback systems, retries, escalation to humans — without losing the trace of what was done and why.

  • Self-healing plan execution
  • Multi-tool fallback strategies
  • Confidence-aware autonomy
  • Full decision provenance
GOAL Q3 close PLAN 4 tasks EXECUTE + replan OUT COME
Verifiers and evaluators

A second opinion, every time

Independent verifier agents check work before it commits — catching hallucinations, policy violations and arithmetic errors before they reach your systems.

  • Policy-bound verifiers
  • Numerical / logical checkers
  • Hallucination detection with grounding requirements
  • Eval suites with offline scoring
Agent proposes Confidence 0.91 Human approves in Slack / Teams Action executes audited
Reasoning approaches

Single-shot prompting vs. true planning

Where each approach lands when used in production enterprise workflows.

Capability
Without xyner
With xyner
Multi-step task handling
Brittle
Native
Failure recovery
Manual
Dynamic replanning
Explainability
Limited
Per-step trace
Verifier loops
Rare
Built-in
Cost budgeting
DIY
Per-workflow
Confidence thresholds
Ignored
First-class
The replanning behaviour is what makes this real. Our procurement workflow now self-heals through three different ERP failure modes.
Director, Procurement Ops · Global CPG
FAQ

Common questions, straight answers.

How is xyner different from a chatbot platform?

Chatbots respond. Agents act. xyner' agents take real actions in your systems — post journal entries, create tickets, route approvals, run SQL — under policy and with full audit.

Can we deploy on-prem or in a sovereign cloud?

Yes. xyner offers multi-tenant cloud, dedicated VPC, hybrid, full on-prem Kubernetes packaging, sovereign cloud, and air-gapped installations — including UAE and Oman residency.

How long does a typical deployment take?

4-6 weeks to first production workflow using a starter pack (Finance, HR, ITSM, Procurement, Support). Custom agents typically 6-12 weeks depending on integrations.

How do you handle prompt injection?

Guardrails are enforced outside the model — policy-as-code, tool allowlists per agent, output validation, redaction, and approval gates. We also run adversarial red-teaming against every release.

Get started

Ready to put autonomous agents to work?

See xyner in your environment with a guided executive demo.

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Keep exploring

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Reference architecture for xyner.ai: control plane, data plane, agent runtime, memory, integrations.

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Monitoring & Alerting

Live monitoring, SLAs, KPIs and proactive alerts for every production agent.

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xyner.ai

The autonomous agentic AI platform for the modern enterprise. Plan. Reason. Act. At scale.

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