SYNCLOGIC
Agent map
Record each agent’s mandate, inputs, outputs, tools, model and handoff conditions.
Many agents. One conclusion. Who is it safe to rely on?
SyncLogic audits the entire reasoning pathway across agents, hand-offs and tools so you know how the final conclusion was composed, where it can fail, and what's safe to be used for.
Bring transparency, accountability and assurance to multi-agent AI systems so you can trust the final output — at the right level, for the right use.
Maps the entire agent ecosystem
Traces the reasoning pathway across hand-offs
Tests alternatives and contradictions between agents
Finds the weakest link that limits reliability
Assigns a Reliance Class (RC 0–7)
Issues a Permission-to-Rely verdict for the final output
The same disciplined method, applied to this claim type: define, decompose, register evidence, test admissibility, explore alternatives, find the weakest link, assign reliance, and issue a verdict.
Clarify the objective, scope, constraints, audience and decision the output will inform.
What exactly is the system trying to achieve?List all agents, tools, models, data sources and orchestrations involved.
Who/what is involved and what is their role?Document the full flow: inputs → decisions → outputs across every agent and tool.
How did the final conclusion come to be?Evaluate quality, relevance and scope of all data, prompts, instructions and retrieved information.
Was each input fit for purpose and within scope?Identify assumptions made by each agent and whether instructions caused bias or narrowing.
What assumptions were made or inherited?Did the system consider alternatives? Are there conflicts between agents or models?
What alternatives were tested or missed?Locate the step, agent, assumption or data point that most limits reliability of the final output.
Where could the conclusion break first?Rate overall reliability based on evidence strength, uncertainty, dependency depth and sensitivity.
How much reliance is justified for this output?State what the output can be used for—and at what level (explore, inform, decide, act).
What is this output safe to be used for, right now?Create a transparent audit record others can inspect, challenge and reproduce.
Can others see, test and reproduce the audit?We verify continuity, scope and intent at every hand-off.
Scope Lock keeps the system anchored to the original task.
We check what was filtered, summarized or transformed.
We surface hidden assumptions and test their impact.
We evaluate fitness-for-purpose of each agent and tool.
We detect, test and resolve contradictions transparently.
We identify who (or what) introduced key decisions.
Multi-agent systems may be complex. Trust doesn't have to be. Audit the system. Understand it. Then decide what is safe to rely on.
This is an illustrative method example, not a completed client audit or an independently validated finding.
Record each agent’s mandate, inputs, outputs, tools, model and handoff conditions.
Trace every material claim back through the synthesis to the source selected by the research agent.
Check whether qualifiers, exclusions, dates and jurisdiction survived each transfer.
Use an independent agent or session to challenge the dominant recommendation and source set.
The review agent receives the synthesis but not the original source register, so it cannot independently verify evidence fit.
Suitable as a draft research workflow after repair; not suitable for autonomous approval or high-consequence release.