Scale the question, not one prompt.
Agents can create bounded sub-investigations when the evidence demands another layer.
Product Swarm Research
Research system / Published runs
Swarm Research
Research beyond the context window.
Swarm Research turns ambiguous, high-value questions into evidence-backed reports. SwarmOS decomposes the problem recursively, sends specialized agents into the evidence in parallel, reconciles contradictions, and preserves the trail behind the final answer.
Technical, market, and company signals in one investigation.
Multi-domain / Open-ended 00 Orchestrator Plan / Route / Review
01Technology
02Supply chain
03Market
04Company
05Evidence audit
06Synthesis
73 domains
119M tokens
Source Claim Contradiction Citation Evidence ledger / Persistent across branches
01 Research workflow
One hard question becomes a research system.
Long context becomes divisible, searchable, and composable. Each branch has a bounded task; the control plane keeps the investigation coherent.
- 01
Frame
Turn an ambiguous decision into explicit questions, claims, and evidence requirements.
- 02
Decompose
Split the question recursively into bounded work for specialized research agents.
- 03
Investigate
Search technical, market, supply-chain, and company evidence in parallel.
- 04
Reconcile
Trace claims to sources, surface contradictions, and route weak evidence back for review.
- 05
Synthesize
Compose the branches into one decision-ready answer with an auditable evidence trail.
02 Published run
Long context, made horizontal.
One SwarmOS investigation mapped Huawei, CXMT, and the China AI stack across technical, supply-chain, and market evidence in about two hours.
Inspect the research architecture- Agents
- 27
- Web searches
- 166
- Pages reviewed
- 200+
- Unique domains
- 73
- Tokens
- 119M
- Elapsed time
- ~2h
03 Control plane
The model is a worker. The system is the product.
The durable capability is the orchestration layer: how work is divided, how agents are routed, how evidence survives, and how quality is reviewed.
Match models to the work.
Use different workers for planning, retrieval, analysis, verification, and synthesis.
Measure the whole outcome.
Compare latency, evidence quality, review effort, and cost per trusted result—not token price alone.
04 Model portability
One control plane. Different model behavior.
The same ambiguous research question was run through two frontier model families. The orchestration stayed constant; delegation depth, token use, and time changed materially.
Operational comparison from published runs; not a controlled benchmark. Worker model Agents Tokens Time
GPT-5.6-Terra 17 35.9M ~1 hour
GPT-5.6-Sol 44 581.2M ~5 hours
05 Evidence, not a demo
Read the work behind the claim.
“Can Huawei's optical telecommunications capability become a risk factor inside data centers—and what could that mean for Lumentum and Marvell?”
Bring us a question too large for one context window.
Explore how Swarm Research can investigate a technical, market, or strategic question with the evidence trail intact.
Discuss a research workload