Raw intent enters
A request starts as normal language, a bug report, a strategy note, or a product direction.
Orchestration visual
Meridian™ turns any AI request into governed delivery: classify the intent, choose the right execution path, route work to the right model, produce durable artifacts, audit the result, hand off context, and keep the whole run searchable - if needed or wanted.
Delivery flow
A request moves from prompt to classification, routing, artifacts, audit, handoff, and searchable recall.
A request starts as normal language, a bug report, a strategy note, or a product direction.
The system separates chat, planning, implementation, review, visual, research, and private/local work.
Deep reasoning, code, visuals, extraction, review, local privacy, and cost-sensitive work can use different models.
The run creates plans, AVDs, ACSs, MPs, code, papers, diagrams, evidence, and follow-up work.
Verification, review, risk notes, and unresolved questions are preserved instead of buried in chat.
Context survives across people, agents, vendors, model changes, and restarts.
Prompts, responses, decisions, artifacts, and evidence can be found and reused later.
Model routing
The important promise is not that Meridian™ uses many models. The important promise is that model selection is governed, visible, and connected to evidence.
Artifact burst
This is where Meridian™ can look unlike vendor chat tools: the visible result is a set of reusable artifacts with lineage, not a disposable transcript.