Synapse Intelligence uses Claude to read DART filings and market data, flag changes and risks, and deliver cited briefings to investors and analysts. Early-stage prototype, built by a solo founder in Seoul.
[23:15:02] INIT Initializing Claude 4.x tool-use loop pipeline...
[23:15:03] INGEST Dynamic 200k context buffer mounted across live market telemetry.
[23:15:04] TOOL-USE Multi-hop database query resolved; output validated against source records.
[23:15:05] EXEC Sandboxed code execution completed. Briefing saved with source citations.
Dynamic Context Processing
Tool-Use Loops with Source Validation
Every claim links to a filing
Long-Context Reasoning & Tool Use
Turning long, dense Korean filings into short, checkable briefings.
Continuous monitoring of real-time securities, corporate filings (DART/SEC), and macroeconomic indicators. Synthesizes risk alerts and summaries with links back to the original filings.
Ingests proprietary internal knowledge, policy documents, and research papers into living, self-compounding wikis. Empowers cross-functional teams with multi-hop reasoning.
Specialized micro-agents execute sandboxed Python/SQL routines, compile analytical briefings, and synchronize databases with a human review step before anything is acted on.
REST APIs, WebSocket feeds, unstructured PDF archives, and corporate databases.
Dynamic steerability, 200k context caching, and recursive multi-agent consensus.
Verified code execution, automated filings, and secure executive intelligence delivery.
Why modern enterprises trust the Synapse Intelligence multi-agent framework.
Harnessing industry-leading code intelligence and reasoning benchmarks to perform multi-hop document synthesis while preserving semantic nuance.
Event-driven micro-agents listen to edge webhooks, financial feeds, and proprietary vault documents, running on a schedule via Cloudflare Workers, with safety guards.
Agent actions are limited by permission boundaries and kill-switches. Data is sent only to the Anthropic API; we do not claim air-gapped operation.
Synapse Intelligence relies fundamentally on Anthropic's steerability, deep code understanding, and 200K context window. Our multi-agent workflows route high-difficulty reasoning traces through Claude 4.x models (Sonnet-class for orchestration, Haiku-class for high-volume extraction), with citations back to source documents so humans can verify every output.
Illustrative format of a generated briefing (sample, not live customer data). Demo video / repository link: available on request.
Status: working prototype (multi-agent runtime + Cloudflare Workers scheduler), preparing closed beta. Figures below are planning estimates, not measured production data.
| Workload | Model tier | Est. tokens / month |
|---|---|---|
| Filing and document synthesis (DART/SEC, 100k-token contexts, prompt caching) | Sonnet-class | ~30M |
| Bulk extraction and classification of feeds | Haiku-class | ~50M |
| Agentic tool-use (SQL/Python sandbox, briefing generation) | Sonnet-class | ~20M |
| Total (beta phase) | ~100M |
Reliability approach: structured tool-use, source citations, schema validation and human-review checkpoints. We do not claim error-free output.
Pioneering autonomous reasoning systems and cognitive architectures.
Alumnus of Korea Advanced Institute of Science and Technology (KAIST). Builds LLM agent tooling for Korean financial disclosure analysis.