Threat intelligence that surfaces what matters, without the noise.
Deduplicate external reporting, map it to the organization’s technology and exposure, and produce source-grounded action briefs.
Nothing is finalized until a human approves it.
Where the time and money actually go.
Teams receive too many advisories and feeds; generic summaries lack asset relevance, duplicate the same event, and do not translate into owned actions.
Threat analysts, SOC, vulnerability, executives and business owners
Trigger to act: Intelligence consumption is high but action is low, new regulations/industry threats increase executive demand, or an MSSP needs tailored client briefs.
The result you can model before you sign.
Illustrative only: 4 analysts × 50 feed-review hours/month removed × $90 loaded hourly cost = $18,000 monthly capacity. Intelligence value depends on action and coverage.
The outcome, plainly: Deduplicate external reporting, map it to the organization’s technology and exposure, and produce source-grounded action briefs.
Inputs in. A cited, review-ready result out. Your expert decides.
A Permission-aware RAG copilot. Every material fact is grounded in an allowed source and returned with its identifier, with no invented data.
Claude Sonnet 4.6 or GPT-5.6 Terra for complex grounded work; select by task-level evaluation; Gemini 2.5 Flash, GPT-5.4 mini or Claude Haiku 4.5 for high-volume routing and drafting. PostgreSQL + pgvector or managed vector store; Policy rules and evaluator service.
- Advisory/report
- Source reliability
- Indicators/TTPs
- Affected products
- Client assets
- Exposure
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.
Analysts validate attribution, relevance, urgency, indicators, and recommended action; external intelligence is never treated as confirmed local compromise.
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.
The category is crowded. Most of it isn’t built for your workflow.
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.
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.
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.
- ✓ One process / scope
- ✓ Live workflow on your data
- ✓ Baseline evaluation suite
- ✓ Measured vs. current process
- ✓ Full scope & integration
- ✓ Human-review UI & audit trail
- ✓ Write-back to your systems
- ✓ Production evals & monitoring
- ✓ Multi-facility rollout
- ✓ Advanced security & compliance
- ✓ Custom control & escalation
- ✓ Dedicated evaluation program
10,000 to 35,000 grounded questions per month; indexing and vector search.
Planning assumptions, not vendor quotations. Your threat feeds and other platform licenses are separate and owned by you. Figures confirmed during scoping.
“His vast knowledge of technologies and a natural problem-solving mindset consistently lead us through complex challenges with clarity and confidence.”
Questions serious buyers ask.
Does the AI act on its own?
No. Analysts validate attribution, relevance, urgency, indicators, and recommended action; external intelligence is never treated as confirmed local compromise. The system drafts and recommends; a human approves every consequential action. Explicitly excluded: no unsupported attribution; no active targeting or offensive use; no claim that an indicator alone proves compromise; no redistribution beyond source license.
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 $500 to $3,800 per month (10,000 to 35,000 grounded questions per month; indexing and vector search), plus a $2,600 per 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. You need an approved API/cloud billing account. Workspace seats are optional for internal prototyping and administrator access.
How is this different from Recorded Future?
Tools like Recorded Future, Mandiant, and CrowdStrike Intelligence 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 is live, and how do we prove it works?
We baseline the relevant-item precision first, then measure against that baseline. You see the scorecard before expanding scope: the evaluation suite ships with the system, not as an afterthought.
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