RAG retrieves fragments. RLM reasons over everything. Load entire document sets into a reasoning runtime and run focused extraction passes — no chunking, no vector search, no information loss.
Every page
No manual filtering
Feed in entire contract portfolios, regulatory libraries, or codebases — no pre-processing required
BYOM
Bring your own model
OpenAI, Anthropic, Google, OpenRouter, or your own local LLMs — no vendor lock-in
Full visibility
Built-in observability
Real-time dashboard tracking every query, every dollar, and every model decision
RAG systems chunk your documents, embed them into vectors, and hope the right fragments surface at query time. RLM takes a fundamentally different approach — a JavaScript REPL layer that loads full source corpora into memory. The model iterates over complete documents, tracks provenance, and synthesizes results with audit-ready outputs.
Built for teams that need verifiable intelligence across large, evolving document sets.
RLM Runtime Flow
REPLLoad
Ingest full document corpus into the reasoning runtime
Extract
Run targeted passes over complete source material
Refine
Iterate and improve outputs with each successive pass
Export
Deliver structured results with full provenance tracking
Every capability built to deliver control, repeatability, and transparent intelligence for enterprise teams.
RAG pipelines lose context at every step — chunking, embedding, retrieval. RLM keeps the full source available for every reasoning pass, eliminating the information gaps that make RAG unreliable.
Run targeted passes that progressively improve answers, summaries, and extractions. Each iteration builds on the last with full auditability, giving you confidence in every output.
Run OpenAI, Anthropic, Google, or any model via OpenRouter — or connect your own local LLMs. Consistent tooling, policies, and outputs across every provider. Zero vendor lock-in.
Review contracts, policies, and regulatory filings at scale. RLM processes entire document sets with precision, delivering traceable results that compliance teams can verify.
Navigate large repositories, system diagrams, and architectural decisions with full context. Map dependencies, surface patterns, and generate documentation across millions of lines.
Synthesize market intelligence, scientific literature, and internal reports in minutes. Cross-reference entire corpora to surface insights that manual review would miss.
Enterprises don't deploy AI they can't monitor. RLM ships with a dedicated observability dashboard that gives your team full visibility into every query, every model decision, and every dollar spent — in real time.
Queries today
Avg latency
Cost today
Success rate
Query volume (24h)
1,247 total
Model routing
Recent queries
Track every query in real time — success rates, token usage, iteration counts, and context bytes. Filter, search, and drill into any execution.
See spending by model, team, and time period. Set daily and monthly budget thresholds with automated alerts before you exceed limits.
Monitor p50, p95, and p99 latency across providers. Compare model performance side-by-side and identify bottlenecks before they impact users.
Understand how your team uses RLM. Surface common query patterns, token efficiency, and context size distribution to optimize workflows.
Connect and monitor multiple RLM deployments from a single dashboard. Test connectivity, compare performance, and manage instances centrally.
Export full query history in CSV or JSON with one click. Every query, every pass, every output — ready for audit review at any time.
RLM is built for organizations that demand control over their data, models, and compliance posture. Every deployment includes enterprise-grade security by default.
Deploy with full data isolation, retention policies, and access controls. Your documents never leave your environment.
Every query, every pass, every output — logged, searchable, and exportable. Meet compliance requirements with zero additional effort.
Self-host on your infrastructure or deploy to your cloud. Full control over networking, scaling, and model access.
Set spending thresholds by team, project, or model. Real-time cost tracking with automated alerts before you exceed limits.
Talk to Hampton about deploying RLM for your team. Custom engagements tailored to your data, governance, and scale requirements.
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