AN Alpesh Nakrani
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Cybersecurity · Cycle-time reduction

Ask your SIEM in plain language without the query-language tax.

Translate analyst questions into transparent, permissioned queries, explain the returned evidence, and preserve the exact query for review.

◆ human-gateda person approves every consequential action
$24,000
fixed-scope pilot
Specialist opportunity
launch posture
Strong durable demand
market signal
natural-language-siem-investigator
// clarify intent
input: Analyst question
step: inspect schema
citations: [ source ✓ ]   confidence: 0.93
HUMAN GATEawaiting review →

Nothing is finalized until a human approves it.

Built for
The buyer
CISO, SOC Director, MSSP CTO
The champion
Security Analytics Director, SIEM Engineering lead, Threat Hunting manager
Day-to-day users
SOC analysts, threat hunters, incident responders, auditors

Designed, built, and evaluated by Alpesh Nakrani, VP of Growth at ViitorCloud, 14 years shipping software, writing on AI-Native engineering and evaluation.

Evals-first
built in from day one
Human-gated
judgment stays with you
The problem

Where the time and money actually go.

Analysts must know vendor-specific query languages and table schemas; query mistakes waste time or produce misleading conclusions.

Who feels it

SOC analysts, threat hunters, incident responders, auditors

Trigger to act: SIEM migration or analyst onboarding is active, multiple query languages are used, hunting capacity is low, or MSSP analysts switch across tenants.

Outcome & ROI

The result you can model before you sign.

Illustrative, replace with your data
$17,000
per month, illustrative

Illustrative only: 40 analysts × 5 query hours/month removed × $85 loaded hourly cost = $17,000 monthly capacity. Query quality must be validated on a schema-specific gold set.

The outcome, plainly: Translate analyst questions into transparent, permissioned queries, explain the returned evidence, and preserve the exact query for review.

Time to first valid query
Query success
Result relevance
How it works

Inputs in. A cited, review-ready result out. Your expert decides.

A Read-only security investigation agent. Every material fact is grounded in an allowed source and returned with its identifier, with no invented data.

01
Clarify intent
02
Inspect schema
03
Generate bounded query
04
Estimate cost
05
Require preview
06
Execute read-only
07
Summarize evidence with limitations
08
Save query
09
Attach to case
Reference architecturegrounded · human-in-the-loop · fully auditable
Source systems · scoped access
SIEM/data lake
Schema/catalog
Identity/RBAC
Saved query library
Detection content
Grounded reasoning core
Retrieve & extract
grounded on your sources, returns citations
Reason & draft
Claude Sonnet 4.6 or GPT-5.6 Terra
Human gateAnalyst approves query and interpretation; destructive commands are impossible; broad/high-cost or sensitive searches require elevated approval.
Action · only after approval
Attach to case
Audit trace
sources, rules, confidence, reviewer
Tenant isolation
minimum data, never cross-tenant
Evaluation suite
baselined pre-launch, watched after
Observability
cost, latency & drift telemetry
Model strategy

Claude Sonnet 4.6 or GPT-5.6 Terra, selected on the client’s code/security golden set; deterministic scanners, policy rules and tests remain authoritative; use a smaller model for labeling only. Read-only tool adapters; sandboxed execution; static analysis / test framework.

Inputs
  • Analyst question
  • Authorized tenant/time range
  • Schema
  • Query examples
  • Data quality
  • Returned events
The human gate

AI-Native, not autonomous. Judgment stays with your people.

The machine does the work; the human’s role narrows to the one thing that matters, judgment. That constraint is what makes it safe to deploy.

Non-negotiable human gate

Analyst approves query and interpretation; destructive commands are impossible; broad/high-cost or sensitive searches require elevated approval.

What it will never do
Read-only by design
No unrestricted query generation, cross-tenant access, evidence deletion, or claim that a generated query proves absence of compromise
The scorecard

A scorecard, not a demo. We baseline what breaks in production.

Every deployment ships with an evaluation suite. These are the numbers we baseline before launch and monitor after.

Primary
Time to first valid query
Query success
Result relevance
Cost/scan control
Permission violation
Analyst correction
Saved-query reuse
False conclusion
Why this, not that

The category is crowded. Most of it isn’t built for your workflow.

The alternatives
Microsoft Security CopilotSplunk AI AssistantGoogle SecOps GeminiElastic AI AssistantPantherDevocustom text-to-SQL/SPL/KQL tools
This implementation

Fixed-scope, tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in from day one. A price you own, not a subscription you rent.

✓ Fixed price, not a seat subscription ✓ Grounded in your data & rules ✓ Human approval on consequential actions ✓ Auditable decision trace
Systems & integrations

It plugs into the stack you already run.

No rip-and-replace. Access is scoped to the minimum data necessary, isolated per tenant, and fully logged.

SIEM/data lakeSchema/catalogIdentity/RBACSaved query libraryDetection contentCase systemQuery cost controlsTenant isolation
Pricing

Transparent by design. The build price buys the workflow and the proof.

A fixed implementation fee plus a monthly bill that scales with volume and governance. No hidden seats.

Pilot
$24,000
one-time · bounded proof of value
  • One process / scope
  • Live workflow on your data
  • Baseline evaluation suite
  • Measured vs. current process
Most chosen
Production
$56,000
one-time · full deployment
  • Full scope & integration
  • Human-review UI & audit trail
  • Write-back to your systems
  • Production evals & monitoring
Enterprise
$94,000
one-time · multi-entity / regulated
  • Multi-facility rollout
  • Advanced security & compliance
  • Custom control & escalation
  • Dedicated evaluation program
Monthly operating cost

25,000–1,000,000 security events/month; SIEM/export charges can dominate.

$1,550–18,200
usage (models, OCR, vector, storage)
$3,800/mo
managed evaluation & monitoring

Planning assumptions, not vendor quotations. Your SIEM and other platform licenses are separate and owned by you. Figures confirmed during scoping.

On working with Alpesh
“His vast knowledge of technologies and a natural problem-solving mindset consistently lead us through complex challenges with clarity and confidence.”
AM
Adil Multani
Senior Backend Developer
Why this is safe to try
01Baseline first. We measure your current numbers before we build anything.
02Fixed scope, fixed price. One process in the pilot. No open-ended engagement.
03Expand only if the scorecard earns it. You see the measured result before committing to production.
04Your people stay in control. The human gate means nothing consequential happens without a human’s approval.
FAQ

Questions serious buyers ask.

Does the AI act on its own?

No. Analyst approves query and interpretation; destructive commands are impossible; broad/high-cost or sensitive searches require elevated approval. The system drafts and recommends; a human approves every consequential action. Explicitly excluded: Read-only by design; no unrestricted query generation, cross-tenant access, evidence deletion, or claim that a generated query proves absence of compromise..

How do you stop it inventing facts?

Every material claim is grounded in an allowed source record and returned with its source identifier. The system separates observed facts, model inference, and missing information, and routes to a human whenever confidence is low, evidence conflicts, or an adverse outcome is possible.

What does it cost to run each month?

A usage bill of roughly $1,550–18,200/month (25,000–1,000,000 security events/month; SIEM/export charges can dominate), plus a $3,800/month managed retainer for evaluation, monitoring and maintenance. Your existing platform licenses are separate and already yours. Exact figures are confirmed during scoping.

Do we need a ChatGPT or Claude subscription?

No consumer ChatGPT or Claude subscription is required for the production workflow. The client needs an approved API/cloud billing account. Workspace seats are optional for internal prototyping and administrator access.

How is this different from Microsoft Security Copilot?

Tools like Microsoft Security Copilot, Splunk AI Assistant, Google SecOps Gemini are broad platforms you adapt to. This is a fixed-scope implementation tuned to your systems and rules, grounded in your data, with the human gate and audit trail built in, and a transparent price instead of a seat subscription.

How long until it’s live, and how do we prove it works?

This is a specialist opportunity. We baseline “Time to first valid query” first, then measure against that baseline. You see the scorecard before expanding scope: the evaluation suite ships with the system, not as an afterthought.

Book a scoping call

Bring your real numbers. Leave with a fixed-scope plan.

A 30-minute engineering-led working session, no slideware. You leave with a sized opportunity estimate, a fixed-scope pilot plan, and the integration & human-review path mapped.

VP of Growth at ViitorCloud · senior delivery owner confirmed before paid work

Ask AI about Natural-Language SIEM Investigator