An open data lake, every SOC workflow, and the AI agents to run them.
Every platform forces a trade-off — visibility vs. budget, retention vs. speed, AI vs. cost. SOC teams stitch six tools that don't talk, pay a per-GB ingest tax, and drop logs on the floor to keep the bill down.
One platform — replacing SIEM, SOAR, UEBA, and the detection engine — on an open lake you already own, driven by AI agents your analysts govern.
Three planes — Interface, Platform, Lake — woven together. Agents move freely across all of them.
Ask the question once. LogSeam turns it into an evidence-backed assessment, recommended actions, and ready-to-use outputs, so analysts move from investigation to decision without stitching tools together.
884,349 failed auth attempts on three high-value targets from Tor and proxy infrastructure. Organized and persistent — not opportunistic.
71% tactic coverage. Strong on Initial Access; thin on Defense Evasion and C2. Eight new Sigma rules drafted with backtests.
12 of 18 TTPs covered. Six gaps in OAuth abuse and cloud lateral movement — both observed in recent campaigns. Two suspect matches in your data.
Every security event, from every source, landed as columnar Apache Parquet on object storage — your bucket or ours, with unlimited retention and no proprietary lock-in. Read by any SQL tool.
Ingest is just the first step. Every event is compressed, optimized, indexed, catalogued, and continuously understood — so by the time you query, the lake already knows what's in it.
Raw JSON normalized and packed into columnar Apache Parquet — 10–20× smaller, fast to scan, cheap to keep forever.
Bloom filters, page indexes, statistics, dictionary encoding — queries skip everything they don't need.
Partitioned, tiered, and compacted for your access pattern. Hot is fast, cold is cheap, no re-architecting.
Every dataset registers in an open catalog with schema, partition spec, and time-travel snapshots.
Continuously studies the lake — what each column means, how values relate across sources. Schemas drift; the catalog keeps up.
Whether your data starts in a SIEM, an EDR, a SaaS, or a custom app, it ends up here — landed as open Parquet, read by any tool that speaks SQL.
Export colder data into LogSeam for long-term retention and lightning-fast search. Drop-in S3 destinations preserve your original SIEM schema as open Parquet.
Centralize telemetry from every security tool. Open formats ensure permanent access without vendor lock-in. Unified retention with intelligent tiering and enterprise RBAC.
Add LogSeam as your durable, cost-efficient destination. Simple S3-compatible target config with high-throughput, low-latency ingestion.
Single S3-compatible endpoint for all environments. Automatic schema-on-read and global replication. Any source that outputs JSON, in minutes not months.
One runtime replaces SIEM, SOAR, UEBA, and the detection engine — with economics that don't punish you for ingesting data.
Detection, response, hunt, and intelligence on one runtime. Stop paying four vendors and stitching their APIs to get one outcome.
Predictable per-compute-node pricing. No per-GB ingest tax, no per-query meter, no surprise bill when alert volume spikes.
Apache Parquet on object storage you already own. No per-GB ingest fees, no cold-tier surprises, no egress charge when you leave.
A workflow can call a workflow. An agent can call a workflow. A pattern can feed a rule. One runtime, one audit trail, infinite combinations.
A small query gets a small footprint. A petabyte hunt gets a fleet. LogSeam adapts the compute envelope to the request — automatically, per query — and accelerates everything with distributed SQL, smart caching, and entity tables.
Per-query elastic compute means the engine right-sizes itself to the work. One analyst's quick search runs cheap. The same lake hosting a petabyte hunt runs the same query plan across hundreds of nodes — automatically, with no operator intervention.
Underneath: an advanced distributed SQL planner, smart result caching, and pre-computed entity tables for users, hosts, IPs, and sessions that fold repeated joins into sub-second answers.
A workflow is how repeatable work moves through the platform. Anything can start one — an event, a schedule, an alert, a rule match, an agent. Every workflow scales across the cluster and composes freely with every other.
Workflows live as code, run distributed across the cluster, and chain freely. A workflow can spawn other workflows. An agent can launch a workflow. A workflow can call an agent. Same engine, same audit trail.
Anything repeatable belongs in a workflow — scheduled threat assessments, daily rule reviews, threat-model application against new alerts, intelligence refreshes, evidence packaging at incident close.
Detection-as-code in two complementary forms. Rules cover known TTPs in a single Sigma / SQL match. Patterns chain SQL and analytics steps to model behavior, statistics, and outliers across the entire lake.
Author in Sigma — the open, vendor-agnostic standard — or write SQL directly. Every rule shows a live SQL preview of exactly what will execute. Single-shot match, MITRE-classified, instantly testable.
# sigma rule — admin login from new country title: Admin Auth from Unseen Country logsource: product: okta detection: selection: eventType: user.session.start user.role: admin filter: geo.country: in known_admin_countries condition: selection and not filter
Patterns chain multiple SQL or analytics steps into one detection. Use them for behavioral sequences, statistical baselines, user/host profiling, or outlier hunts across petabyte data.
A growing fleet of purpose-built agents mapped to how SOCs actually work — analyst-grade specialists who answer the questions, operational agents that close the loop, and platform agents that run the room. The harness is open, so you can add your own.
Every event we ingest is linked to the entities it touches — users, hosts, identities, processes, files, IPs, alerts, tickets. When an agent asks "who else touched this account?", the answer is one hop away — not a half-hour pivot through a dozen tools.
Every record is parsed for the entities it references and stitched into the graph — no separate ETL job, no nightly rebuild.
Agents traverse the graph instead of fanning out raw SQL. "Show me everything that touched this account" becomes one query.
Identities from your IdP. Assets from your CMDB. Tickets from your ITSM. The graph reflects your environment — not a generic schema we picked.
Exposed via MCP, SQL, and the API — for your agents, your analysts, and any tool you want to point at it. No black box.
Two layers. Session memory captures the raw work — queries, findings, reasoning. The Library captures curated knowledge — who you are, what you own, who's after you. Investigations compound; compute spend doesn't.
There is no "agent did something" black box. Every tool call an agent makes is a typed action with a caller, a scope, a policy, and an audit record. Sensitive actions wait for a human.
Every tool an agent invokes — query, enrich, ticket, block, isolate, page — is a typed action. Actions carry the caller's identity, the agent that emitted them, scope, inputs, and a policy classification.
Read-only actions auto-execute. Anything destructive — containment, deletion, deployment, ticket creation — pauses for a human approval from the analyst or on-call engineer you've designated. Nothing happens behind your back.
Six interfaces for the work — or skip them entirely and drive everything from your own tooling via MCP. Same lake. Same agents. Same workflows. The Interface is one front-end among many.
Question in, answer out — with the work shown. The fastest way for an analyst to ask anything across the lake. The Assistant searches, runs agents, produces visualizations, and explains its reasoning.
Infinite zoomable workspace. 16 widget types — search, tables, timelines, ATT&CK matrix, entity cards, enrichment. Templates for Phishing, Lateral Movement, Malware. Live cursors and AI copilot on the canvas.
Every alert pre-assessed by the Triage agent with verdict, IOCs, and source logs. Seconds for triage instead of minutes. Every alert reviewed end-to-end before it lands on a human.
Five-phase IR with timeline, evidence management, and the IR agent in every phase. 80% of the report already written when the case closes. The whole team works the incident together.
40+ widget types, custom SQL widgets, per-board AI chat — "why did volume spike?" Real-time metric cards, severity, alert timelines, technique rankings. Multiple boards per team, auto-refresh.
Executive (30s), Compliance (SOC 2 / ISO 27001 / HIPAA in <2min), Incident, Technical — export to PDF/HTML. Or skip the UI entirely and drive every workflow from your own tooling via MCP.
Agents handle the rote — triage, enrichment, correlation. Analysts work the cases that need a human, with full evidence and the work shown.
Rules, patterns, workflows, agents — all composable, all versioned, all in one engine. Build once, reuse everywhere.
Per-node pricing, pass-through compute/storage/AI at cost. Stop dropping data to manage budget.
Strip away the marketing. The engine choice tells you what each platform will be good at.
| Dimension | Traditional SIEM | LogSeam |
|---|---|---|
| Pricing | Per-GB ingest tax | Per-node. Predictable. |
| Storage format | Proprietary index, locked | Open Apache Parquet |
| Storage location | Vendor cloud | Your bucket — or ours, at cost |
| Retention | Hot/cold tiers, fees per tier | Unlimited — one tier, one price |
| Compute | Fixed — pay for idle | Per-query elastic, scales to zero |
| Workflows | SIEM + SOAR + UEBA bolt-ons | One runtime, end-to-end |
| Detection | Single-shot rules | Sigma rules + multi-step patterns |
| AI | Chat bolted on | Agents native to every workflow |
| Memory | No — every question re-queries | Session + Library — investigations compound |
| Governance | Free-form integrations | Typed actions, audit, human gates |
| Egress | Pay to leave | No exit fee — it's your bucket |
Two components. One varies with what you actually run; the other is a flat per-node line for software and support. Compute, storage, and AI are pass-through — at cost, no margin.
EC2-type compute, S3-class storage, and the model providers your agents call — Anthropic, OpenAI, Bedrock, Gemini, MiniMax, Kimi, or self-hosted. Pay your providers directly at your contract rate, or we pass the invoice through at cost — no margin.
One flat rate per node for the lake, the agents, the orchestrator, the UI, and your support tier. Static (always-on) and dynamic (auto-scaled per query) nodes priced separately. A node is any EC2-type compute node, any size.
Sizing depends on the roles your deployment needs: log processing, search, orchestration, and MCP access. Each role can scale independently based on ingest volume, analyst concurrency, workflow load, integration patterns, and the CPU/memory shape of each node.
Ingest, parse, normalize, enrich, and write telemetry into the lake. This tier scales with daily volume and transformation cost.
Interactive queries, hunts, dashboards, and rule execution. This tier scales with analyst concurrency, query shape, and retention window.
Control-plane coordination for schedules, workflow state, cluster membership, and query orchestration. Usually small, but critical.
API and tool-facing nodes for agents, integrations, and MCP clients. This tier scales with automation volume and external access patterns.
→ Each role scales independently · we'll size the node mix to your actual ingest profile and query pattern
LogSeam Managed, your cloud, or on-premises. Every deployment is single-tenant — your own dedicated infrastructure, never shared with another customer.
We run the control plane, the compute, and the lake. You bring data and users. Multi-region available with data residency by region. Fastest time to value.
LogSeam runs entirely inside your own account — fully isolated. Your IAM, your encryption keys, your network policies. We manage the software; you own the perimeter and the spend.
Your hardware, your data center, your air-gap. Self-hosted models supported, no outbound network requirement. Same platform, same agents — custom-scoped pricing.
A demo on your data — with our agents working a real alert end-to-end.