Enterprise AI Platform

Intelligence without context limits

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

Multi-provider model routingFull audit trailZero data retentionEnterprise SLA
How RLM Works

A runtime that treats documents like executable context

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

REPL
01

Load

Ingest full document corpus into the reasoning runtime

02

Extract

Run targeted passes over complete source material

03

Refine

Iterate and improve outputs with each successive pass

04

Export

Deliver structured results with full provenance tracking

Core Capabilities

Engineered for enterprise scale

Every capability built to deliver control, repeatability, and transparent intelligence for enterprise teams.

Unlimited context

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.

  • No token limits on input
  • Zero truncation or summarization loss
  • Full source grounding for every output

Iterative refinement

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.

  • Multi-pass reasoning chains
  • Progressive accuracy improvement
  • Deterministic, reproducible outputs

Bring your own model

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.

  • OpenAI, Anthropic, Google built-in
  • OpenRouter and local LLM support
  • Swap models without changing workflows
Use Cases

Built for high-stakes analysis

Compliance & Legal

Enterprise document analysis

Review contracts, policies, and regulatory filings at scale. RLM processes entire document sets with precision, delivering traceable results that compliance teams can verify.

Engineering

Codebase understanding

Navigate large repositories, system diagrams, and architectural decisions with full context. Map dependencies, surface patterns, and generate documentation across millions of lines.

Strategy & Research

Research acceleration

Synthesize market intelligence, scientific literature, and internal reports in minutes. Cross-reference entire corpora to surface insights that manual review would miss.

Observability

Enterprise observability, built in

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.

H
RLM by hampton.io
Live

Queries today

1,247+12%

Avg latency

1.2s-8%

Cost today

$18.40

Success rate

99.4%+0.2%

Query volume (24h)

1,247 total

Model routing

OpenAI
39%
Anthropic
30%
Google
20%
Local LLM
11%

Recent queries

Summarize Q4 compliance filings1.1s
Extract key clauses from vendor contract0.9s
Cross-reference regulatory changes1.4s
Analyze codebase architecture dependencies2.1s

Query analytics

Track every query in real time — success rates, token usage, iteration counts, and context bytes. Filter, search, and drill into any execution.

Cost intelligence

See spending by model, team, and time period. Set daily and monthly budget thresholds with automated alerts before you exceed limits.

Performance profiling

Monitor p50, p95, and p99 latency across providers. Compare model performance side-by-side and identify bottlenecks before they impact users.

Prompt pattern analysis

Understand how your team uses RLM. Surface common query patterns, token efficiency, and context size distribution to optimize workflows.

Multi-instance management

Connect and monitor multiple RLM deployments from a single dashboard. Test connectivity, compare performance, and manage instances centrally.

Compliance export

Export full query history in CSV or JSON with one click. Every query, every pass, every output — ready for audit review at any time.

Enterprise Ready

Security and governance from day one

RLM is built for organizations that demand control over their data, models, and compliance posture. Every deployment includes enterprise-grade security by default.

Data governance

Deploy with full data isolation, retention policies, and access controls. Your documents never leave your environment.

Complete audit trail

Every query, every pass, every output — logged, searchable, and exportable. Meet compliance requirements with zero additional effort.

Deployment control

Self-host on your infrastructure or deploy to your cloud. Full control over networking, scaling, and model access.

Budget management

Set spending thresholds by team, project, or model. Real-time cost tracking with automated alerts before you exceed limits.

Get Started

Ready to process unlimited context?

Talk to Hampton about deploying RLM for your team. Custom engagements tailored to your data, governance, and scale requirements.

We respond within one business day.