Turn agent work intoinstitutional memory.

Memco remembers the fixes, dead ends, and decisions behind successful agent work, so the next agent gets the shortcut your team already paid to discover.

Read the research

Enterprise memory, without giving up control.

SOC 2On-prem optionsGDPR-readyYour code stays yours
The memory loop
From one-off runs
to trusted memory

The simple idea:
every useful run should
teach the next one.

01
Starting cold

Agents repeat work when lessons stay trapped in the session.

A new run has to rediscover repo quirks, failed paths, and human corrections. The agent may look smart, but the company gets no smarter.

Cold-start taxRepeated debuggingLost corrections
02
Capture

memco turns agent work into trusted memory.

Fixes, corrections, failed paths, and repo conventions become scoped, reusable lessons. Work your team already paid for starts helping future agents.

ProvenanceScope controlNo workflow change
03
Compounding

The next run starts ahead of the first.

When a similar task shows up, the agent gets the prior fix, warning, or decision before it burns tokens rediscovering it. Waste goes down as trusted memory gets richer.

Less rediscoveryFaster completionMore predictable runs
04
Control

Enterprise memory stays inside your boundaries.

Teams decide what becomes memory, who can reuse it, and where it can run, with deployment options that fit regulated environments.

SOC 2On-prem optionsGDPR-ready
Works with
your agent
stack
Models
ClaudeGPTGeminiLlamaDeepSeekQwen
IDEs
CursorWindsurfCopilotZedVS CodeJetBrains
Install
ROI calculator

See what Spark saves your team

Shared memory cuts token usage by ~50% and eliminates wasted reruns. Plug in your numbers.

Daily token spend per engineer
Annual token savings$469K50% reduction in repeated-context costs
Developer hours saved3,125 hrs~1.6 full-time engineers
ROI multiple54xFor every $1 spent on Spark
Spark Teams costs $9K/yr for your team — saving you $469K.

Model portability

Your memory is the asset.Models come and go.

Every successful agent run leaves behind a trace — a fix, a dead end, a decision. Memco turns those traces into an organizational asset that compounds over time. The model underneath is interchangeable; switching is a swap, not a migration.

What the benchmarks show

Proof in numbers.

50%
Lower cost per task · same model
98%
Recommendation hit rate
48%
Faster to task completion
53%
Fewer tokens per task
SWE-Bench variant · DS-1000 · Spark teams benchmarks · arXiv 2511.08301
Start with the memory gap

Turn today's
agent work into
memory your company
can reuse.

Book a pilot Research Docs