AI Context Relay Infrastructure · Context That Arrives Intact

Your AI workflow is only as good as the context it passes.

Pass the right context to every AI step. RelayLum sits between agents, models, tools, and memory — moving a luminous Context Capsule that holds customer queries, account facts, and tool results, then filters, compresses, and verifies what each hop may see.

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Support Agent

Ingest & extract

Billing Tool

Enrich status

Policy Agent

Scrub & compress

Response Agent

Deliver packet

Context Capsule Node 1 · Support
Issue Double charge on invoice Customer Acme · Pro plan Plan Annual · active Action Issue refund

Inside capsule: customer query · account info · tool results

Sources: Slack #support · CRM account · billing API

Timestamps: 14:02 ingest · 14:02 extract · permissions: support+

Path: Support → Billing → Policy → Response

Current hop

Support Agent — fact extraction

  • Customer dialogue reduced to Issue, Customer, Plan, Requested Action
  • Raw thread kept out of the next hop
  • Permissions stamped on every fact
Full record vs Relay packet
Direct pass
12,480 tokens · PII in thread · stale plan note
RelayLum packet
1,140 tokens · scrubbed · current billing only
Session savings
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Run the relay to the finish line to light the path and see tokens saved.
Context handoff failures

Eight breaks RelayLum is built to stop

01

Incomplete transfer

One agent’s conclusions never fully reach the next.

02

Token bloat

Whole conversations pile up — cost climbs for nothing.

03

Contradictory facts

Different agents get conflicting customer information.

04

Temporal confusion

Old memories mix with the latest data.

05

Attribution gap

The model uses data but cannot name the source.

06

Debug blindness

After a failure, you cannot tell which hop lost context.

07

Read-everything waste

Every agent reads all available data — slow and expensive.

08

Handoff drift

Summaries slowly deviate from original facts across hops.

RelayLum is not an agent builder, not a vector database, and not a generic logging platform. It is the infrastructure that turns raw information into Context Packets shaped for the next task.

How a relay works

Four hops. One intact packet.

01ExtractTurn messy conversation into stamped facts — Issue, Customer, Plan, Action — with source and time.Support
02EnrichPull live tool results. Expired subscription rows are marked — never silently reused.Expired flagged
03Scrub & compressPolicy removes unnecessary personal fields and packs the rest into a small Context Packet.Policy
04DeliverResponse Agent receives only what it needs — with a full provenance path for every claim.Traceable
The relay stack

Open any station on the light path

Source Gateway Relay Engine Context Packets Provenance Trace Compression Lab Context Evals Memory Gateway

Built for AI agent companies, intelligent support products, research assistants, enterprise copilots, and automation platforms.

Pass The Right Context To Every AI Step

Context that arrives intact — not more context, the necessary context.

RelayLum sits between agents, models, tools, sessions, and memory. It turns raw inputs into Context Packets optimized for the next hop — compact, reliable, and fully traceable.

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