Cadenya vs Cerenovus: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Cadenya and Cerenovus — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Cadenya

Paid

A managed agent runtime that layers your tools, agents and objectives so teams can test agent behavior safely and iterate fast.

Unified Tool Layer: Connect MCP servers, OpenAPI specs and existing endpoints once, and expose them to every agent through a single managed interface.
Model-Agnostic Variations: Set a default model and run canary variations on other providers side by side to compare behaviors before promoting a change.
Progressive Tool Discovery: Tool schemas stay out of the context window until an agent asks for them, with configurable max tools per search, search hints and a rerank threshold, so every request gets smaller.
Live Token Metering: Track cost as it accrues across loops, active variations, memory entries and widgets, so usage is visible rather than discovered on the invoice.
Webhooks and SSE Streaming: Push agent events — assistant messages, tool results, approval requests, sub-agent spawns, compaction, timeouts — into your own apps in real time.
Memory Layers: Attach stored documents such as playbooks and policy sets to an agent so its guidance persists across objectives.
Outcome Feedback Scoring: Collect scored comments on each objective, attributed to the variation and model that produced it, to see which behaviors actually work.
Embeddable Widgets: Drop an agent experience into any frontend as a widget rather than building the conversational surface yourself.

Operational Exception Handling: Run an agent that detects stalled shipments or orders and reroutes them through your dispatch API within policy.
Safe Model Migration: Evaluate a new frontier model as a canary variation against live objectives before switching the default.
Wrapping Existing APIs: Turn internal OpenAPI endpoints into agent-callable tools without rewriting the services behind them.
Embedding Agent Chat in a Product: Ship a conversational agent surface into an existing frontend using widgets instead of building it in-house.
Cost Control at Scale: Use progressive discovery and live metering to keep context size and per-loop cost down as agent traffic grows.
Agent Quality Review: Compare scored feedback across variations to understand which prompt or model changes improved real outcomes.

Paid

AI operating partner that reads enterprise records to surface hidden inefficiencies and warn about breaking systems, every claim cited.

Cited Findings: Every claim opens downward to the original document — a quote that cannot be found in its source never enters the record, so audit and legal can trust each line.
Inefficiency Detection: Surfaces duplicate payments, missed discounts, zombie software seats, dormant vendors, stalled receivables, and process patterns that quietly drain margin.
Early-warning Signals: Flags promises past deadline with no fulfilling event, accounts whose rhythm broke, renewals about to close at last year's usage, and processes that stopped running.
Time-aware Ledger: Answers what was believed vs what was actually true at any past date, so last quarter's company is still queryable — critical for audits and post-mortems.
Independent Review Loop: Every finding is checked against its sources before it reaches the user; anything unresolved goes to a human reviewer instead of being silently dropped.
Numbers With Workings: Each figure ships with the calculation and the source documents behind it, so any line can be rerun, checked, or opened for evidence.
Zero-install Ingestion: Reads the records a company already produces with no installation and no user interviews required.
Segmented Solutions: Purpose-built jobs for Enterprise, Middle Market, Private Equity, Consulting, Secondaries/Continuation Vehicles, and Corporate M&A/Integration teams.

Margin Recovery Sweeps: Find duplicate vendor payments, missed early-pay discounts, and idle SaaS seats in weeks-of-history without a consulting engagement.
Process Bottleneck Discovery: Identify approval chains that reject nothing but add weeks, or work items that always route through one bottleneck person.
Executive Early Warning: Give CEOs, CFOs, and COOs a standing early-warning system so problems reach them while they're still small and cheap to fix.
Deal-side Due Diligence: PE, M&A, and integration teams can query years of a target's records for hidden risk with every claim cited to the source document.
Consulting Delivery Acceleration: Advisory firms use Cerenovus as their inspection layer so questions that used to take weeks of digging get an evidence-backed answer in minutes.
Complex Exit Support: Secondaries and continuation-vehicle sponsors get a time-aware record they can defend to LPs and auditors.