Adapt vs Xalgorix

Adapt and Xalgorix are both ai agent apps 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.

Adapt

The vendor describes Adapt as an autonomous business intelligence agent that connects to disconnected data sources, routes queries to optimal models, and surfaces answers directly in Slack — without requiring SQL or dashboard-building skills. For executive briefings and churn monitoring, the no-code workflow layer handles the repetitive retrieval work so analysts are not the bottleneck. The credit-based free tier lets teams validate integrations before committing. The scraped page content provided does not match the tool — it describes a travel identification app called Spotter — so specific integration names, connector counts, and workflow depth cannot be verified from the source material and are omitted here.

Xalgorix

The core loop is detect, chain, verify: the agent runs reconnaissance through injection through authentication testing, then executes a dedicated validation phase before anything reaches your report. On a public deliberately-vulnerable target, the vendor documents 9 verified findings including a CVSS 9.8 RCE in 17 minutes. The REST API and cron-style scheduling let security teams wire scans directly into CI/CD gates, so releases block on verified findings rather than scanner noise. Where the architecture shows its limits: scan depth and concurrency are credit-gated, and teams running continuous coverage across a wide attack surface will need to budget credits carefully. Self-hosted deployment is listed as an option for teams with data-residency requirements.

Attribute	Adapt	Xalgorix
Pricing	Paid	Paid
Price	—	from $1 per scan
Free trial	No	No
Open source	No	Yes
Has API	Yes	Yes
Self-hosted option	No	Yes
Platforms	Slack, Web App	Web dashboard, REST API
Pros	Autonomous cross-system data retrieval, so a director can ask a churn question in Slack and get an answer without queuing an analyst request — eliminating the 24–48 hour turnaround that makes weekly reviews stale by the time they land. No-code workflow automation for recurring tasks like daily briefings and ARR monitoring, which means the ops or RevOps lead can own these workflows without pulling engineering into every change. Slack-native delivery, so insights surface in the channel where decisions are already being made rather than requiring a context switch to another BI tool that leadership checks once a quarter. Model routing that selects the optimal LLM per query type, so you are not paying GPT-4 rates for a simple metric lookup or getting weak results on a complex attribution question because the model was set globally. Credit-based free tier with no credit card required, so a team can connect real data sources and run actual workflows before making a budget commitment — reducing the risk of buying a demo that breaks on production data.	Exploit-verified findings only — the validation phase confirms each vulnerability with a working proof-of-concept before reporting, so engineers fix real risk instead of auditing a noisy candidate list. REST API with programmatic scan creation and report retrieval, which means CI/CD pipelines can gate releases on verified findings without a human in the review loop for every build. Cron-style recurring scans provide continuous attack surface coverage, so a newly deployed endpoint does not wait for the next manual engagement to get tested. Branded PDF reports include executive summary, severity breakdown, proof-of-concept, and remediation steps with dated evidence, which means audit deliverables are a direct export rather than a manual writeup. Self-hosted deployment option means organizations with data-residency requirements or air-gap mandates can run the platform without routing target data through the vendor's infrastructure.
Cons	No self-hosted deployment option means any team operating under data residency mandates, SOC 2 audit requirements, or internal policies against third-party cloud access to production data cannot use Adapt without a policy exception — and teams in that position typically move to a self-hostable alternative rather than negotiate exceptions for every data source. The no-code workflow layer works for linear retrieval tasks, but multi-step workflows with branching logic — for example, 'if churn score exceeds threshold, pull support ticket history, then cross-reference contract renewal date, then route to the right CSM' — push past what visual no-code builders handle cleanly; teams building that level of conditional logic typically end up adding a code layer alongside Adapt, which means two systems to maintain. Connector coverage is not disclosed publicly, so teams with niche or internally built data sources have no way to verify compatibility before signing up — the free credits test period becomes mandatory validation rather than optional exploration, and an unsupported source means a stalled rollout.	Multi-target scans process sequentially, not in parallel — a queue of ten applications runs one at a time with full state recovery between jobs. Teams needing simultaneous coverage across a large asset inventory hit this ceiling immediately and either reduce scope per run or build a scheduling layer on top of the API to manage the queue themselves. Scan depth and breadth are credit-gated, with no fixed monthly allocation described in the docs. Teams running continuous coverage on a wide attack surface face unpredictable credit burn during high-change deployment periods, and the only mitigation is manually narrowing phase selection or scan frequency. The 22-phase methodology is fixed by the vendor — you can focus on subsets of phases, but you cannot inject custom test logic or extend the agent's toolset. Security teams with proprietary attack patterns or bespoke application architectures that require custom modules will hit this wall and move to a platform that exposes the agent's tool layer for extension, such as an open framework where the testing logic is fully configurable.

Bottom line

Xalgorix is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Adapt and Xalgorix?

Adapt is Paid, while Xalgorix is Paid and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Adapt better than Xalgorix?

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.