Cignara vs Quadratic

Cignara and Quadratic are both business tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Cignara

Cignara deploys AI agents that handle inbound voice and chat support from first contact through resolution, following your SOPs and policy rules without a human stepping in for every edge case. The platform is built for large B2C contact centers where call volumes make per-interaction staffing costs unsustainable. It also surfaces upsell signals mid-conversation, so revenue opportunities that a tired agent would miss at hour six of a shift are captured automatically. The ceiling appears when your workflows require judgment calls that fall outside documented policy — the agent follows rules well, but writes none of its own. Teams with highly variable, exception-heavy interactions report needing significant policy documentation work before the system handles them reliably.

Quadratic

Quadratic is a spreadsheet environment where cells can hold Python, SQL, or JavaScript instead of formulas, and an AI agent writes that code from plain-English prompts. You connect live sources — Postgres, Snowflake, QuickBooks, Plaid, Mixpanel — and the sheet stays in sync without CSV exports. The AI handles joins, forecasts, and charts; you review the generated code before it runs, so there is an audit trail. The ceiling appears when your analysis requires orchestration across multiple agents with complex branching — the spreadsheet model stops fitting the logic. Teams at that point reach for a dedicated workflow tool and keep Quadratic for the output layer.

Attribute	Cignara	Quadratic
Pricing	Paid	Paid
Free trial	No	No
Open source	No	No
Has API	No	Yes
Self-hosted option	No	No
Platforms	Cloud-based SaaS; phone and chat channels	Web
Released	2022	—
Pros	Agents complete multi-step support interactions — rescheduling, refund processing, billing disputes — autonomously end to end, so your human team handles exceptions rather than volume. Policy-driven execution means a compliance or SOP update propagates through agent behavior without rebuilding workflow logic, which prevents the drift between your documented process and what the system actually does. Real-time copilot mode feeds live suggestions to human agents mid-call, so the productivity benefit extends to interactions that do require a person rather than stopping at automation. Multi-channel coverage across voice and chat from a single platform, so you avoid running separate automation stacks that produce inconsistent customer experiences across contact methods. Upsell and cross-sell signal detection runs during live interactions, which means revenue opportunities surface at the moment they are relevant rather than in a post-call analytics report nobody acts on.	AI writes Python and SQL from plain-English prompts, so analysts who know what they want but not the syntax stop being blocked — and the generated code is visible in the cell, which means a reviewer can verify the logic instead of trusting a black box. Live connections to Postgres, Snowflake, BigQuery, QuickBooks, Plaid, and Mixpanel mean the sheet refreshes from source data, so you stop chasing down who last exported the CSV and whether it was before or after month-end close. MCP support lets external agents write to and read from the spreadsheet as a tool, so Quadratic can sit inside a larger agent pipeline rather than requiring you to rebuild your entire workflow inside one product. Output lives in a familiar spreadsheet format, so sharing results with a finance director or product manager who will not open a Jupyter notebook is not a conversation you have to have. Replacing VLOOKUP stacks with readable Python reduces the 'who wrote this and why does it break' debugging cycle — the logic is explicit, versioned, and survives column-order changes.
Cons	The agent follows policy it is given — it does not generate or infer policy for novel situations. Teams with high exception rates or loosely documented SOPs spend significant time on policy engineering before the system handles real call volume reliably; this work is invisible in the demo and surfaces in the first production month. There is no self-hosted deployment path and no public pricing or trial access. Enterprises with data residency requirements that rule out vendor-hosted infrastructure have no workaround — this is the condition under which teams move to a self-hostable competitor rather than continuing the sales conversation. The platform targets large enterprise contact centers, which means the onboarding and sales process is calibrated for procurement cycles. Teams at mid-market scale or those needing a working proof-of-concept before budget approval are structurally excluded from evaluating it.	Multi-step conditional logic — branching on what a previous query returned, then routing to a different data source based on the result — does not fit the spreadsheet execution model. Teams building that kind of workflow hit this ceiling on the second or third agent and add a separate orchestration layer, at which point they are maintaining two systems. No self-hosted deployment option means every live database connection and every piece of data processed by the AI agent transits Quadratic's cloud. Teams under strict data residency requirements or with security policies prohibiting third-party cloud access cannot use the product and move to a self-hostable alternative. The API and scheduled tasks are paid-only features, so teams evaluating the free tier for automated, recurring reports will find those capabilities gated — the evaluation environment does not reflect what production actually requires. The product targets analysts in a spreadsheet paradigm; engineers building data pipelines or transformation logic that belongs in dbt, Airflow, or a dedicated ETL tool will find the canvas constraining and the collaboration model mismatched to a code-review workflow.

Bottom line

Only Quadratic exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Cignara and Quadratic?

Cignara is Paid, while Quadratic is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Cignara better than Quadratic?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.