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SynthBoard

Complete guide

What is AI-powered
decision intelligence?

Decision intelligence turns what you know into what to do next. SynthBoard runs it in two steps: your facts on file, each with its source — then experts who argue the options and hand back one call, with the dissent kept.

Start free See how it works

An example: the facts she keeps, each with its source — then the board’s call on them.

In short

What is AI-powered decision intelligence?

AI-powered decision intelligence is a discipline that applies artificial intelligence — multi-agent systems, structured disagreement and structured analysis — to improve the quality of strategic decisions. Instead of one model’s answer, it puts several AI experts with different viewpoints on the same question and returns one recommendation, with a confidence that drops when they split.

The term was popularized by Cassie Kozyrkov, formerly Chief Decision Scientist at Google. Business intelligence answers what are the numbers? Decision intelligence answers given these numbers, what should we do — and what could go wrong?

It starts from
Your facts. What you tell her stays on file with its source, marked when it has aged, yours to correct or wipe.
Who argues
One named expert for a narrow call; a board of opposed seats, on different AI models, for the biggest ones.
What comes back
The call, the conditions it holds under, who disagreed and why, and a first step with a date. Confidence is never above 90.
What it costs
One expert reads up to 65 credits on its card; a board on Free, up to 135 credits.

Two decisions

The numbers say what happened.
The room says what to do.

A subscription business losing revenue, and a family deciding whether to buy. One went to a board, one to a single expert. Examples, trimmed for length.

Three ways to win back revenue

Work · Board of 3

Our coffee subscription lost 15% of revenue in two quarters. Churn went from 3% to 5.2% a month after we raised the price from $19 to $24. Roll the price back, add a cheaper plan, or send a win-back discount?

Chief of staff

Your numbers are on file — the price change, the churn, the 2,400 subscribers. This is a board call: The CFO, The Customer and The Analyst. Each researches alone first, then they react to one another.

  • The CFOFinancial Controller
  • The CustomerUser Voice
  • The AnalystData Expert

Asked first

Is the churn spread across everyone, or mostly people who joined at $19?

Mostly the $19 joinersAcross the boardI don’t know yet

The board’s call

Keep $24, add a $16 every-other-month plan, and offer it to everyone who cancels.

The churn sits with subscribers who joined at $19: they are leaving the price, not the coffee. A cheaper cadence keeps them without repricing the 2,400 who stayed; a rollback gives back $5 a month on every account to save a few hundred.

Confidence67 · Moderate

The Customer disagreed

“A cheaper plan reads as a downgrade. Ask ten people who left before you build it”

First step Email last month’s 140 cancellations the every-other-month planThursday

Board of 3 · up to 135 credits on the card · an example, not a recorded run

Rent, or buy now?

Life · One expert

We pay $2,300 a month in rent. A two-bedroom near work costs $520k, we have $95k saved, and mortgages are around 6.4%. Buy now, or rent two more years?

Chief of staff

One expert is enough for this: The Analyst puts the bad, likely and good cases on one page. I’ve kept your rent and savings on file for next time.

  • The AnalystData Expert

Asked first

How sure are you that you’ll stay in this city for seven years?

Very sureProbablyNot sure

The call · The Analyst

Rent two more years, and save $1,500 a month toward a bigger down payment.

At 6.4%, owning costs about $3,400 a month before upkeep — $1,100 more than rent — and buying only wins if you stay seven years or more. Two more years of saving takes the down payment past 20%, which drops the mortgage insurance.

One expert · up to 65 credits on the card · an example, not a recorded run

How AI does decision intelligence

Your facts, opposed seats,
one call you can act on.

Research on collective intelligence — Scott Page’s diversity prediction theorem, James Surowiecki’s work on crowds — finds that diverse views beat uniform expertise when the diversity is structured. A board is the structure; a memo that keeps the dissent is how it adds up.

Opposed seats, on different models

Each expert researches alone, then reacts once to the others. On a decision, two take opposed sides, and the seats are spread across model families — OpenAI GPT-5, Anthropic Claude, Google Gemini, xAI Grok — so one model’s blind spots don’t become the call.

Sized to the question

Not every call needs a board. She answers the small things herself, puts one named expert on a narrow question — about a minute — and convenes a board for the biggest calls.

It reads where your numbers live

She reads Stripe, Google Sheets, HubSpot and more, and says what she read. Your tools are read-only until you allow writing, and every write is a preview you confirm (Pro and above).

The call becomes a first step

Every memo ends in a first step with a date. It waits under Open and gets one check-in on its day.

Compared

Decision intelligence vs.
business intelligence.

Business intelligenceDecision intelligence
FocusWhat happened?What should we do?
Time orientationBackward-looking: historical dataForward-looking: the options in front of you
Core outputDashboards, reports, metricsA call, the risks, the trade-offs, a first step
AI roleAggregating and charting dataArguing the options from different seats
Handles ambiguityPoorly — needs structured dataNatively — built for hard trade-offs
Competitive analysisMarket-share metricsWhat a rival does the day after you move
How you use itView and filter dataQuestion and challenge the experts

BI tells you revenue dropped 15%. Decision intelligence weighs the ways to win it back — and says which, and why.

The landscape

Decision intelligence tools,
side by side.

Single-model AIEnterprise DI platformsBI platformsMulti-expert DI
ExamplesChatGPT, Gemini, ClaudeCloverpop, Rainbird, QuantexaTableau, Power BI, LookerSynthBoard.ai
Best forQuick questions, writing, researchOrganizational workflows, compliance, data integrationData visualization, historical analysisStrategic decisions, investment analysis, product strategy
LimitsAgreeable by default, one perspective, no structured disagreementEnterprise sales cycle, high cost, complex setupBackward-looking; no reasoning about what to doNeeds a clear decision question

Who sits

Who argues your numbers.
Each one holds a position.

Your Chief of Staff proposes who sits for the call, and every board is built with someone whose job is to argue against the obvious answer. Name an expert and they take a seat; tell her who you want on your board and they sit by default. How many seats a board has depends on your plan.

Pick an expert

Hover, tap or tab throughSwipe, then tap one
  • GPT
  • Claude
  • Gemini
  • Grok

Seats are spread across model families: GPT, Claude, Gemini, Grok and more.

Questions

Fair questions.
Straight answers.

What people ask about decision intelligence.

What is AI-powered decision intelligence?

AI-powered decision intelligence is a discipline that applies multi-agent AI systems, structured analysis, and structured disagreement to improve the quality of strategic decisions. Unlike single-AI tools that provide one perspective, decision intelligence platforms assemble multiple AI experts with different viewpoints to surface hidden risks and produce synthesized recommendations.

How is decision intelligence different from business intelligence?

Business intelligence (BI) is backward-looking — it analyzes historical data to understand what happened. Decision intelligence is forward-looking — it analyzes options, risks, and tradeoffs to help you decide what to do next. BI tells you your revenue dropped 15%. Decision intelligence helps you evaluate three strategies to recover it.

Why does multi-agent AI produce better decisions than a single AI?

Every AI model has blind spots and biases from its training data. A board spreads its seats across different AI models (OpenAI GPT-5, Anthropic Claude, Google Gemini, xAI Grok) with different reasoning frameworks, creating cognitive diversity that catches what any single model would miss. Research in collective intelligence consistently shows that diverse perspectives outperform uniform expertise.

What is AI sycophancy and why does it matter for decisions?

AI sycophancy is the tendency of language models to agree with users rather than challenge them. Models trained with RLHF optimize for user satisfaction, which means they tell you what you want to hear — not what you need to hear. For strategic decisions, this means confirmation bias with AI-generated confidence. Multi-agent systems solve this structurally by assigning experts competing objectives.

How does a board show where experts agree and disagree?

After the experts research alone and react once to each other, the memo shows where they agree, where they split, and the confidence behind the call — a structured signal about which aspects of a decision are settled and which need more investigation. SynthBoard does not reduce a board to one agreement score: its confidence drops with dissent and is never rated above 90, and the memo keeps the dissent itself — who disagreed, why, and what would change the call.

Who uses AI decision intelligence tools?

Founders and CEOs making strategic pivots, product managers prioritizing roadmaps, investors evaluating deals, consultants advising clients, and anyone facing a high-stakes decision with multiple valid approaches. Decision intelligence is valuable wherever the cost of a wrong decision is significantly higher than the cost of structured analysis.

How do I get started with AI-powered decision intelligence?

SynthBoard.ai offers a free tier with 150 credits every month plus 250 to start. Tell your Chief of Staff the decision; she answers what she can herself, and when a call needs judgment she proposes a consult with one named expert or a board of several, priced on a card before anything runs. A memo with the board’s call, the conditions it holds under, who disagreed and why, the risks, and what would change the call. Its confidence drops with dissent and is never rated above 90. Your first move becomes a commitment with a date.

Next

Decision intelligence on specific calls, and the reading behind it.

SynthBoard (synthboard.ai) is one place for your business, your life, and every hard call. Your Chief of Staff keeps what you tell her on file, and 24 named experts on different AI models take the calls — one expert for a consult, a board with opposed seats for the hard ones — and hand back a memo with the call, the dissent and the first move. How it works.

Your facts first.
Then the call.

Churn rose after our price riseRent two more years, or buy now?Build it in-house, or buy the tool?

It waits in her box after you sign up. Nothing is sent until you press send.