xanber · a room full of minds

One AI gives you an answer.
A room gives you a decision.

A generic model hands you the internet's average take. xanber convenes a panel of expert personas who frame the problem, argue it out, and hand back one answer you can act on.

Five people seated around a table in a meeting room, each with a nameplate, deliberating over a wooden block marked DECISION.
the room · live
StrategistFastest path is to ship the enterprise tier first.
SkepticAgainst what evidence? Support can't staff it yet.
MarketerPositioning's untested. Pilot with three accounts.
SynthesisPilot first, staffed by two, decision-gate in 30 days.
why the room wins

Five things a single model can't do

01

Every persona is properly framed

Each persona arrives with a defined role, real objectives, domain expertise, your organisational context, and the constraints it has to work within — the difference between asking a stranger and briefing an executive who already knows your business.

The research is pointed here: a throwaway "act as an expert" label does little on its own. What moves the needle is depth and fit — and stacking several well-built personas rather than one. That's exactly what xanber constructs.

Depth > label Persona quality, not the mere presence of a role, is what improves reasoning — and more well-designed personas compound the gain. Zheng et al.; Kong et al., 2023
02

Many lenses, not one voice

Real decisions pull in finance, legal, risk, product, and operations before anyone commits. xanber does the same — specialists read the problem from genuinely different angles before converging.

And it has to be genuine difference. In head-to-head tests, a diverse panel beat several identical copies of the same model by a wide margin.

91% A diverse panel hit 91% on the GSM-8K reasoning benchmark; three identical copies of one model reached only 82%. Diversity of Thought, 2024
03

They debate before they answer

The first answer is rarely the best. Personas challenge assumptions, expose weak spots, critique each other, and refine toward consensus — so blind spots get caught before anything reaches you.

Structured debate is one of the most robust findings in recent AI research, and it works precisely because agents share the why, not just the verdict.

70→95% Multi-agent debate lifted accuracy from roughly 70% to 95% while measurably cutting hallucination. Du et al., 2023
04

Grounded in your world

Generic AI knows the world. xanber can know your organisation — your documents, policies, knowledge base, past projects, and terminology — so you get advice that fits, with sources you can trace.

Grounding answers in your own verified data is the single most effective known defence against confident-but-wrong output.

~40–47% Typical reduction in hallucination when answers are grounded in retrieved data — with visible provenance. Enterprise RAG benchmarks, 2025–26
05

It works, it doesn't just talk

Most AI stops at text. xanber personas can connect to your systems — retrieve, update records, generate reports, trigger approvals — inside the guardrails and human sign-off you set.

The market has moved from AI that suggests to AI that acts, and the returns are real for teams that automate well-defined work under oversight.

~171% Average ROI reported on agentic AI deployments; Gartner expects 40% of enterprise apps to embed task-specific agents by end of 2026. Deloitte 2026; Gartner
the result

Informed, contextual, debated answers — traceable to the reasoning behind them.

Smarter decisions, made with more confidence, without pasting the same prompt into five tabs.

Step into the room → free starter tier · no card required