calibrating prism…

SPECTRA
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[ dispersion engine — v4.2 ]

Raw in.Resolvedout.

Spectra sits between your chaotic event stream and the people who operate on it. It ingests the noise — logs, topics, lake files, drifting schemas — and disperses it into three sharp bands your team can act on before lunch.

throughput
0.0 M evt/s
resolve p95
0.0 s
trust
SOC 2 · EU
fig. 01 — dispersion prism

[ sys.01 — the problem ]

Your lake
is not
a lake.

← in / chaos

  • 19 Kafka topics, 4 naming conventions, 0 owners
  • Parquet partitions landing late, twice, renamed
  • plan_tier drifted varchar → json on a Friday
  • Revenue dashboard disagrees with itself by 18%
  • Three teams maintain three definitions of “active”

out / resolved →

  • One intake. Every source typed, timed, owned.
  • Drift quarantined before it reaches a dashboard.
  • Revenue, risk, freshness — verified, with confidence.
  • Each insight ships with an owner and a next step.
  • “Active” defined once. Enforced everywhere.

Fig. 02 — The prism does not store your chaos. It refuses to pass it through.

[ sys.02 — proof ]

Measured
in prod,
not slides.

0M evt/s

sustained intake

peak 7.2M, no backpressure

0s p95

raw → resolved

from 40 min batch window

0%

insight confidence

verified, drift excluded

0%

join cost cut

median, first 90 days

[ sys.03 — sequence ]

Three
passes.
No noise
survives.

Numbered because order is the product: nothing can be resolved before it is ingested, nothing ships before it is verified.

  1. 01

    Ingest

    Connect Kafka, S3, Postgres, CDC and webhooks in an afternoon. Every byte gets a timestamp, a source and a schema fingerprint on arrival.

    kafka → intake · s3 → intake · cdc → intake

  2. 02

    Disperse

    The prism splits the stream: normalize types, quarantine drift, join facts, kill duplicates. Chaos enters; three clean bands leave.

    normalize · quarantine · join · dedupe

  3. 03

    Operate

    Revenue, risk and freshness land where work happens — warehouse marts, Slack, your dashboard — each with an owner and a confidence score.

    mart · alert · owner · confidence

spectra — resolve --watch● live
$ spectra connect kafka://prod --topics raw_* ✓ 19 topics
$ spectra watch --band revenue_7d
  intake      4.81M evt/s   schema fp a4:91:c2
  quarantine  plan_tier drift → held   dashboard untouched
  resolved    €4.82M · conf 99.1%   owner: m.okafor
$ spectra ship --to warehouse.marts ✓ fresh 4 min ago

why teams switch

“Our Monday numbers meeting went from ninety minutes of arguing about definitions to ten minutes of deciding. The prism ate the argument.”

— Data platform lead, Series D fintech
1.2B events/day · 6 sources · live since March

[ sys.04 — telemetry ]

The bands,
plotted
weekly.

Same three bands as the prism fan: revenue resolved, risk owned, freshness verified. Drawn from one pilot cohort, not a benchmark lab.

Resolve time fell from 40 minutes to 1.9 seconds

p95 raw → resolved · seconds, log scale · 24 pilot weeks

40m10m1m5sBATCH ERAPRISM ERA1.9s

F3 Hairline Area · Pilot cohort · 2026

Throughput holds 4.8M events a second

sustained intake · M evt/s · 30 days prod

4M5M6M7Mavg 4.7Mpeak 7.2M — no backpressure

F2 Hairline Line · Prod EU-West · 2026

Every heavy join costs less after dispersion

compute cost · $/day · before / after · median customer, 90 days

0$500$1000$1500$2000−38%orders ×events−38%inventory ×suppliers−40%sessions ×users−44%payments ×refundsBEFOREAFTER

F6 Paired Rungs · Billing export · 2026

[ sys.05 — compare ]

Three ways
to lie to
yourself.

Two of them are industry standard. Dimensions a platform team actually argues about.

dimension

diy lake + dbt

warehouse-native

spectra ◢

First insight
9 months
5 months
2 weeks
Schema drift
fails silently
alerts only
quarantined
“Active” defined
3 versions
1 per dept
once, enforced
You pay for
sprawl
seats + compute
resolved events

[ sys.06 — stack ]

Sits beside
your stack.

  • Kafka

    intake · CDC

  • S3

    lake files

  • Postgres

    CDC outbox

  • Snowflake

    marts in

  • BigQuery

    marts in

  • dbt

    tests stay green

  • Slack

    alerts + owner

  • PagerDuty

    freshness SLO

Fig. 03 — No rip-and-replace. Spectra reads what you already emit and writes where you already look.

[ sys.07 — faq ]

Asked by
every CTO.

Q1Do we rip out our warehouse?

No. Spectra sits beside it. Intake reads Kafka, S3 and Postgres CDC; resolved bands land back as versioned marts. Your warehouse stays the system of record — it just stops receiving garbage.

Q2Where does our data live?

Where you put it. EU or US region, single-tenant intake, SOC 2 Type II. Raw payloads are typed and fingerprinted at the edge; nothing trains shared models.

Q3Raw intake is free — where is the catch?

There is none to find. We charge per resolved event that ships with an owner and a confidence score. Noise you send us costs you nothing, which is also why we are motivated to turn it into signal.

Q4What if the pilot numbers do not hold?

You keep the audit: schema fingerprints, quarantine log, confidence report. If resolve p95 or confidence miss the agreed thresholds, the pilot costs nothing.

[ sys.08 — access ]

Feed the
noise.

Pilot in two weeks: we connect one source, resolve one band, and prove confidence on your own data. If the numbers do not hold, you keep the audit.

SOC 2 Type II · EU residency available · No rip-and-replace, sits beside your stack

  • Week 1One source connected. Intake verified against your lake.
  • Week 2First band resolved. Confidence report on your definitions.
  • Day 30Three bands live. Owners assigned. Old dashboards retired.
  • PriceUsage-based on resolved events. Raw intake is free — we only charge for signal.
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