Thalamus Advisory
Buying an observability platform does not create resilience, any more than buying a treadmill creates fitness. We build the operating practice — measurement, escalation policy, evidence, and the organisational habits that survive contact with a bad night — supported by two products designed around it.
The position
Every organisation in the sectors we cover is putting probabilistic systems into paths with physical, clinical, financial or political consequence. The question that decides whether that goes well is not how good the model is. It is whether the system around the model can detect and survive a wrong answer.
An investigation agent that always produces an answer is one an attacker can choose the answer for. Conclusions must arrive with evidence and a confidence score, and low confidence must change what happens next.
Self-verification produces correlated errors — the same training distribution, the same blind spots. Challenge must come from a different model, with authority to force human escalation.
Safety implemented as a sentence in a prompt is advisory. Guardrails belong at the execution boundary, enforced by infrastructure the model cannot talk its way past.
Retain the probes, their results and the agent-to-agent chain. The artefact a regulator asks for is the reasoning; the conclusion is only its summary.
Products
ThalamusTrace raises a correlated problem. Thalamus SRE investigates it, challenges its own conclusion, and routes a decision. Either works alone; together they close the loop from signal to remediated change without a human in the middle of the boring part.
OTLP-native ingest for traces, metrics and logs — the OpenTelemetry standard rather than a vendor agent, which is also what keeps your data portable back out again.
An agent fleet over that telemetry, with the boundary between automated and escalated set by you rather than by us.
Both products provision as managed instances — pooled or dedicated tenancy, per region, from one console — or deploy self-hosted inside your VPC, data centre or accredited enclave where the data is not permitted to leave. In regulated and classified estates, self-hosted is not a preference but an eligibility requirement, and the architecture was designed around it rather than accommodating it afterwards.
How we engage
Most organisations do not need a tool first — they need to find out how bad the problem currently is, which is a measurement exercise. Every engagement below produces a number you did not previously have.
Reconstruct 30–50 recent incidents and measure the overturn rate of initial hypotheses, time lost to misdirected remediation, and how often the eventual cause sat outside the observable estate.
Whether your estate can support automated investigation at all: instrumentation coverage, retention against investigation latency, trace continuity across seams, and the diagnostic query paths that will be exercised at volume.
Where user-controlled data enters logs, which agents read those logs, and what authority those agents hold — delivered as a ranked remediation list.
Your time-from-onset-to-investigation distribution plotted against current retention, with a tiered model sized to your real error ratio. Usually reduces cost while increasing diagnosable coverage.
Re-investigate incidents previously closed as unreproducible, using correctly anchored windows. Typically recovers several genuine root causes — and writes the business case for everything else.
Deployment against a bounded service domain, guardrails configured to your risk posture, escalation treated as a success state, and the overturn rate tracked from day one.
Sector-specific engagements — clinical path mapping, regulatory evidence readiness, pre-peak resilience audits, OT/IT boundary observability, enclave deployment design — are described in each sector’s issue.
What we will not do
A partner who will not say no is a supplier, and you already have those.
Start a conversation
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