Team view — fundraise slides hidden
Confidential · July 2026

Memory for AI agents that developers own — cited, exactly replayable, and built to travel across models.

Seed Briefing

Team Primer

What we're building, who it serves first, and what ships now.

$6–8M Seed

Confidential · July 2026

The Problem

Agents forget — and no one can prove why they act.

Agents forget

Context is rebuilt ad hoc — per tool, per vendor, per session. None of it travels with the developer.

A lived example

Maya runs Cursor, Claude Desktop, and two CLI agents on the same product. Tuesday she decides the deploy-checklist rule is wrong. Wednesday, three agents still behave as if the old rule is true — and she cannot show which prior run saw which instruction.

Decisions are unprovable

When agents act on memory, no one can show what they knew, where it came from, or why they acted.

A lived example

Sam is on-call. An agent took a bad action at 14:12. Leadership asks: what did it know? Today the answer is guesswork over chat logs.

Vendors are capturing memory

Major foundation-model providers are making memory native to their own accounts and platforms.

What vendor "import" looks like today

Anthropic's March 2026 cross-vendor import is a prepared prompt dump — lossy and unverifiable. A prompt-grade dump is not a recipient-checkable move of your memory.

The Product

The neutral, replayable memory layer for agents that need to outlive any one vendor.

write attributable memory assemble grounded context record the decision correct future context without rewriting history

An assembly is the exact package of memories the agent was shown before it acted — and SegnoLabs records every one.

Own it, don't rent it

Content-addressed memory the developer controls — not an asset locked inside one model provider. (Content-addressed: every record is named by a fingerprint of its content, so anyone can verify it hasn't changed.)

Provable, replayable decisions

What it knew, where that came from, why it acted. Recorded assemblies exactly replay.

A credible portability path

Model-independent records. Closure-verified export ships today shipped — verified round-trip import is the next gate roadmap.

Today working write → assemble → cite → correct → exact-replay path, on SQLite and Postgres. Now proving design-partner workflows, verified import, repeatable deployment.

Why "Segno"?

Segno is Italian for "sign." In music, the segno marks the exact point a performer returns to and replays from. That is the product: when an assembly is recorded, you can return to that mark and exact-replay what the agent was shown.

Scripted illustration of shipped behavior — not a live engine session
1 · A memory is written
"deploys require checklist v2" · cid:9f2a… · cited to runbook
2 · It is superseded
"deploys require checklist v2"
"checklist v3 replaces v2" · supersedes 9f2a…

The next assemble excludes the old belief.

3 · History still replays
assembly @ Tue 14:12 → re-read returns exactly what the agent saw — unchanged

Correction without amnesia.

Persistent agent memory is now a priced market — the question is who owns it.

One developer wedge. Three proofs of where it leads.

Wedge

The agent fleet that won't stay taught

Maya fixes a rule on Tuesday. On Wednesday three agents still follow the old one — and she can't show which run saw what.

With Segno, her correction takes effect on the next assemble — and history still replays.

Today: capture · assemble · cite · exact replayNext: recant UX · dense recall
Market stakes

Developer-owned AI tooling: people building with agents every day. Lab-native memory deepens lock-in. Explicit note stores and scratchpads snap into routine well — and still aren't a memory product: no grounded assemble over a growing corpus, no exact replay of what the agent was shown, no honest supersession when a lesson is wrong.

Today vs next

shipped content-addressed writes (ingest / MCP memory_write) · deterministic assemble + citations (memory_read) · exact replay of a recorded assembly · supersession-aware gather.

roadmap write-path "recant" UX · dense/hybrid recall.

Not a product attribute yet: "learns what matters" / salience — no mechanism today; it is a research bet, stated as such.

Pilot measure

After a corrected belief is recorded, subsequent assembles exclude it — while a prior assembly that cited the old belief still exact-replays.

Thesis

Switch models without starting over

Priya's team is mid-eval between two model vendors. Leadership asks: if we switch, do we re-teach six months of agent context?

With Segno, memory is a verifiable asset with a credible portability path — not a tenant of one vendor's account.

Today: verified exportNext: round-trip import
Market stakes

Sierra raised a $950M Series E at a $15.8B post-money valuation (May 2026); Salesforce signed to acquire Fin for ~$3.6B (June 2026). The application layer is pricing accumulated agent context as a retention asset. Foundation-model-native memory is the structural bear case: labs cannot be neutral across competitors.

Today vs next

shipped same record identity across SQLite and Postgres · export bundle with cryptographic closure/hash verification — honestly labeled in the engine itself: verified export ≠ verified move.

roadmap round-trip import (gate: re-import preserves cid-set equality) · hosted workspace · dense re-embed without identity change.

The honest portability line: your memories are a verifiable asset with a credible portability path — export is closure-verified today; round-trip import is the next gate.

Pilot measure

Export a workspace and verify the bundle on a clean machine without trusting the sender's service.

Proof

Change its mind — and prove what it knew

Alex's agent keeps citing a stale dependency "fact." The next turn must stop — without destroying the trail. Sam is on-call: "what did it know at 14:12?"

With Segno, an authored correction drops the old belief from later context — while every recorded assembly still reconstructs.

Today: supersession-aware gather · durable assemblies · citationsNext: typed retraction · replay console
Market stakes

Agent product builders and reliability buyers burned by opaque RAG. Mem0 is strong on developer UX; Zep/Graphiti are strong temporal/graph neighbors. Neither publicly offers recipient-side content addressing plus exact replay of the assembled agent context. Platform-embedded audit logs are self-certified — the recipient cannot independently verify.

Today vs next

shipped belief supersession + gather exclude-superseded · durable assembly records + policy identity + citations · exact replay as a property of recorded assemblies.

roadmap first-class supersession write intent · typed retraction records + citation propagation · investigator-facing replay/reconstruct product verbs.

Pilot measure

An authored supersession drops the belief from later gathers — while the 14:12 assembly still reconstructs, byte-cited to its sources.

Roadmap Trajectory

The team's memory is growing

Jordan corrects a runbook belief on Monday. By Wednesday two teammates' agents still assemble the obsolete steps.

Destination: team memory that can grow and heal without forking into tribal lore — requires workspace isolation, sharing gradient, retract propagation roadmap.

Today: same-store sharing (shared bytes) · export handoffNext: workspaces · sharing gradient · safe retract
Market stakes

Team/org segment of developer-owned memory. XTrace ships encrypted-vector search and markets ownership today; Segno's present contrast is deterministic assembly, exact replay, and content-addressed identity. Team sharing is a future collision, not a present product duel.

Today vs next

shipped point two agents at the same store and one engineer's written correction is what the next agent's assemble can see — coincidence sharing, shared bytes only, no ACL/workspace · offline handoff via export bundle.

roadmap workspace isolation · selective sharing gradient · retract propagation — so collective memory compounds without becoming shared stale lore.

Pilot measure

Two agents on one store: a correction written by one is excluded/included correctly in the other's next assemble, and prior assemblies still replay.

These failures are becoming infrastructure problems now, because memory is moving from session convenience to persistent product state.

Supporting cases →

Why Now

Three forces, one window.

The capture race is priced

Sierra reached a $15.8B post-money valuation; Salesforce signed to acquire Fin for ~$3.6B. The application layer is pricing accumulated agent context as a retention asset.

Their strategy is to make accumulated context raise application switching costs; ours is to give developers a record that remains theirs when the application or model changes.

Context integration got legible

MCP has made context integration legible across agent hosts. It lowers distribution friction — a memory server that speaks MCP plugs into MCP-capable clients without per-vendor integration. It does not define how memory is represented, replayed, or verified. That's the layer we build.

Provenance obligations are arriving for high-risk deployments

Teams deploying high-risk AI systems must be able to show what their systems knew (EU AI Act: transparency Aug 2, 2026; Articles 12/26 logging Dec 2, 2027) — a tailwind for teams already required to investigate. Scope honesty: those are Annex III high-risk obligations, not a general mandate — this is never a fines-driven pitch.

The window is open for memory to become neutral infrastructure before it hardens into captive product state.

Defensibility

Provability starts with our own claims: what exists, what comes next, and what evidence closes each gate.

shipped

  • Deterministic assembly — same inputs, same context: reproducible.
  • Exact replay — re-read a recorded assembly and get exactly what the agent saw.
  • Content-addressed records — named by content fingerprint: recipient-verifiable.
  • Supersession-aware gather — a corrected belief drops out of future context; history stays intact.

roadmap

  • Typed retraction + citation propagation.
  • Team sharing gradient with workspace isolation.
  • Round-trip import — the portability gate.

The engine stays private. Trust comes from recipient-verifiable export bundles today, with an open protocol and conformance suite as the trust path. Cross-model neutrality is a wedge a foundation-model vendor cannot credibly lead across its competitors.

Why this is harder than export

Any vendor can export a file. The trust surface is the behavioral contract: canonical records, deterministic assembly, a recorded candidate set and policy for each turn, and conformance that lets an independent recipient reproduce the context that was shown. Our goal is to become the compatibility and evidence boundary for developers operating across vendors — not to claim that the standard is already won.

Competitive one-liners
PlayerThe honest line
XTraceShips encrypted-vector search and markets ownership today; sharing is a future collision. We lead on assemble / replay / identity, not slogan overlap.
FM-native memoryDeepest lock-in; cannot be neutral across competitors; prompt-grade import ≠ verifiable portability.
SierraValidates demand for persistent agent memory as a market fact; foils non-portable lock-in — does not validate our architecture.
Mem0 / ZepStrong UX and temporal/graph neighbors; neither publicly offers recipient-side content addressing plus exact replay of assembled context.

The defensible claim: deterministic assembly + exact replay + content-addressed records + supersession-aware gather shipped; typed retraction + team gradient roadmap. Not "the only developer-owned memory layer."

What about memory standards?

AIMEM, OMS, and PAM contest portable-memory formats. None couples the format to deterministic assembly, a per-turn ledger, and exact replay. We compete on behavioral conformance and interoperable evidence — not on declaring a format winner.

The three hardest questions — answered straight

What stops Anthropic, OpenAI, or Mem0 from shipping portable export tomorrow?
They can ship export, and we assume they will. Export alone is not the product boundary. The differentiated contract is that a recipient can verify canonical records and reproduce the specific context shown to an agent from the recorded candidate set and policy. A foundation-model vendor can improve export, but cannot credibly be the neutral layer across rival foundation models. A memory vendor can adopt the protocol; if it does, that expands the compatibility surface rather than invalidating it.

Why do an open protocol and conformance become a moat rather than a feature?
Not moat-by-openness. The proof point is whether independent implementers and developers use conformance to make memory portable and evidence-bearing across backends and hosts. The private engine gives Segno execution control; the public contract makes its guarantees inspectable. We measure adoption through conforming implementations, verified bundle exchange, and cross-backend replay — no standards victory claimed in advance.

You call this portable, but import is roadmap — what does a customer get now?
Today: developer-controlled, closure-verified export and an attributable record of what context an agent received. That is not yet a completed cross-system move, and we label it accordingly. The next portability gate is round-trip import preserving the cid-set; until then, the immediate value is verifiable ownership and exact reconstruction — not a promise that every destination can already ingest the bundle.

Appendix: living-memory verbs + glossary →

Position & Growth

Begins with one developer. Ends inside the corporation.

1

Individual developer

Adopts SegnoLabs and owns a memory layer that travels across every model and tool they use.

2

Personal circle

Extends selected memory to chosen collaborators and confidants.

3

Teams & projects

Virtual teams across organizations, then formal teams inside a company — shared, project-level memory.

4

The corporation

Company-wide memory management — promoted into an enterprise offering with governance, audit, and control.

Each rung is chosen by the developer — which is precisely why each rung holds.

User: developer → Buyer: engineering / platform leader → System role: neutral memory layer.

Scope honesty: v0 ships rung 1. Rungs 2–4 require workspace isolation, a sharing gradient, and retract propagation roadmap. Go-to-market stays bottoms-up, developer-first.

Team

Built by the people who've shipped this before.

Manas Talukdar

Founder · Technology

  • Two decades in enterprise AI & large-scale data infrastructure
  • Key contributor to the world's preeminent industrial data historian (OSIsoft/AVEVA PI System)
  • Director of Platform Engineering at C3 AI pre-IPO — scaled 6 engineers into a ~30-engineer org
  • Multiple AI/data patents · IEEE Senior Member

Chris

Commercial & Company-Building Leadership

  • CEO of a $140M+-funded enterprise AI company — memory orchestration & RAG for Fortune 50 and U.S. DoD
  • Oracle · Informatica (zero to IPO) · founding-era Salesforce
  • Right Media (acquired by Yahoo, ~$1B) · LevelUp (acquired by Grubhub)
  • Deep relationships across federal markets, enterprise SIs, and the venture ecosystem

Founding engineers — identified and ready. A small group of key founding engineers is lined up behind the round; this seed is what lets us close them and staff the reference implementation from day one.

The Raise

$6–8M seed — three gates this round closes.

1

Product gate

Close the identified founding engineers; ship a production-ready reference implementation with independently testable conformance.

2

Adoption gate

2–3 key development partners complete falsifiable pilots in live workflows — platforms and builders who develop on SegnoLabs and prove the format in production.

3

Expansion gate

1–2 design partners whose live agent workflows harden the memory layer and shape the next product gate.

Named product outcome alongside: verified import parity — the portability gate. Export is closure-verified today; import completes the round trip.

Memory is the asset of the agent era. SegnoLabs makes it something developers own — cited, exactly replayable, and built for cross-model use.

Every recorded assembly leaves a mark. The segno is where you return to replay it.

Ask for the live proof.

Current focus: prove corrected, attributable memory for developers running agent fleets — then expand safely to teams.

Confidential · July 2026

Appendix · presenter discretion

Living-memory verbs — where each stands.

VerbTodayNext
RememberExplicit ingest + MCP write shippedSession/episode bind, capture router roadmap
Learn what mattersNo mechanism — stated plainlySalience / capture-policy design (research bet)
RecallSparse full-text + frozen assemble shippedDense / hybrid / entity-graph retrieval roadmap
Rewrite / recantSupersession-aware gather shippedWrite-path recant UX · typed retract + propagate roadmap
Share across a teamSame-store shared bytes + export shippedWorkspaces · sharing gradient · safe retract roadmap

Glossary — plain words

Assembly
The exact package of memories the agent was shown before it acted. Recorded every time.
Content-addressed
Every record is named by a fingerprint of its content, so anyone can verify it hasn't changed.
Supersession
A corrected belief drops out of future context; history stays intact.
Closure-verified
An export bundle carries proofs that it is complete and untampered — the recipient can check without trusting the sender.
Conformance suite
Public tests any implementation can run to prove it honors the protocol's guarantees.

Appendix · presenter discretion

Supporting cases — later examples, not the alpha customer.

Regulated / high-stakes: an evidence component

A risk engineer must investigate what an agent knew when it acted — in a deployment already in scope for high-risk obligations.

Shipped building block: durable assemblies + policy identity + citations + exact replay of recorded assemblies + export closure verification shipped. Full evidence-pack productization roadmap.

Scope honesty: EU AI Act Articles 12/26 are Annex III high-risk obligations, not a general mandate. This is a technical evidence component for teams already required to investigate — not a compliance certification, and never a fines-driven pitch.

Enterprise knowledge onboarding

A new hire's onboarding agent should inherit institutional runbooks with sources — and drop superseded steps when the runbook changes.

Today: corpus ingest + citations + supersession-aware gather shipped. Dense/entity-graph retrieval + team workspaces roadmap.

Position: an expansion story in a crowded "RAG over the wiki" lane — not a lead wedge.

Confidential · July 2026