Turn technology waste into verified savings.
Siftlogiq helps finance, technology, and AI teams see where money is leaking, decide the safest fix, approve the change, and prove the saving without giving broad write access on day one.
| Business pain | Owner | Saving |
|---|---|---|
| AI prompts repeat expensive context | AI Platform | $4,200/mo |
| Data jobs run bigger than needed | Data Eng | $2,400/mo |
| Unused tools renew next month | Procurement | $1,100/mo |
What each buyer gets.
The website now explains Siftlogiq in business terms first: who benefits, what decision becomes easier, and what proof exists after the work is done.
Know what savings are real.
Verified ledger, forecast, owner, and before/after proof instead of estimates trapped in spreadsheets.
Reduce spend without risky writes.
PR-first or scoped execution, approval gates, blast-radius notes, and rollback contracts for every fix.
Stop token waste while people work.
Prompt cost, cache guidance, model routing, output caps, and quality checks before runaway AI usage reaches the bill.
Approve trust before automation.
Read-only start, customer-managed secrets, redaction, audit exports, and no write action without approval.
Why teams need it now.
Every team is being asked to do more with AI and cloud, but budgets are not unlimited. Dashboards can show spend; the harder business problem is getting the right owner to safely reduce it and prove the result.
AI spend before it explodes
Show prompt cost while people work, suggest cheaper prompt patterns, and prevent runaway token usage before it reaches the bill.
Approved fixes, not advice
Move from “someone should fix this” to Jira, PR, scoped execution, rollback, and owner approval.
Finance-ready proof
Track what was found, who approved it, what changed, and how much money was verified after the change.
What buyers should believe after five minutes.
You do not need another cost dashboard. You need a controlled way to turn cost signals into owner-approved, reversible, finance-verified change.
CTO / Platform
No surprise writes, PR-first fixes, scoped execution, and rollback evidence.
CFO / FinOps
Verified savings ledger with owner, action, before/after impact, and forecast.
Security
Read-only start, data minimization, approval gates, audit export, and admin controls.
From signal to proof, without exposing the console.
This is the story the website should sell publicly. The full console stays behind the secure trial gate.
How savings become business proof.
Instead of asking every leader to read technical reports, Siftlogiq shows a simple chain: pain, owner, approved action, and verified outcome.
The operating story.
Every use case follows the same business-safe path, so a non-technical buyer can understand what happens before access expands.
AI Spend Coach for prompts.
When someone types a prompt in an approved AI surface, Siftlogiq can estimate cost, flag expensive patterns, and show a safer lower-cost version before the prompt is sent.
Before: expensive prompt
“Use the full policy, all ticket history, all customer notes, and produce a long detailed answer for every support case.”
After: guided version
“Use cached policy context, summarize only the latest ticket state, cap the response, and escalate if confidence is low.”
One operating loop for FinOps remediation.
Bring billing, utilization, telemetry, code, architecture, AI usage, data jobs, SaaS seats, and approvals into one controlled workflow.
From signal to controlled change.
Your team gets a familiar FinOps operating loop: inform with accurate signals, optimize with practical recommendations, and operate through governed execution.
Billing, usage, code, AI, data, SaaS, and telemetry signals.
Root cause, owner, service, cost driver, and confidence.
Jira, PR, GitOps, or scoped API execution after approval.
Before/after savings, quality guardrails, and rollback status.
What customers should understand in five minutes.
One business queue showing where money is leaking, who owns it, what can be safely fixed, and what proof finance will receive.
daily useEngineers get the lowest-risk path: PR, Jira, GitOps, scoped API action, or manual execution with rollback notes.
workflow nativeLeadership gets verified savings, forecast, owner accountability, and clean spend trends without reading technical logs.
board readyUse cases buyers recognize immediately.
Each story starts with a business pain, shows what the user sees, and ends with evidence your finance, engineering, AI, and security teams can trust.
AI Prompt Spend Coach
For teams using API gateways, OpenAI, Anthropic, Azure OpenAI, Bedrock, Vertex AI, ChatGPT workspaces, Cursor, Copilot, or internal AI tools, users can see estimated cost while writing and get a cheaper prompt pattern before spend happens.
AI usage is growing faster than budget control. Teams need cost guidance at the moment a prompt, agent step, or model route is chosen.
Inline prompt cost, before/after rewrite, cache guidance, model-route suggestion, max-output guardrail, and quality check before the request is sent.
Cloud service remediation
Your platform team moves from alert fatigue to approved fixes for VM/EC2/GCE sizing, storage lifecycle, NAT/egress, database tiers, schedules, and commitment coverage.
Native cost tools find waste, but implementation still sits in spreadsheets and chat threads.
Each recommendation becomes a ticket, PR, GitOps change, or scoped API action with before/after proof.
Data platform cost control
Your data teams get practical fixes for warehouse size, query filters, partitions, Dataflow workers, autosuspend, retry storms, pipeline schedules, and job-level cost spikes.
Finance sees warehouse spend rising, while engineers need proof that performance will not break.
Every fix carries expected saving, throughput guardrail, owner approval, and verified ledger evidence.
Kubernetes, SaaS, and renewal governance
Your teams can map shared cluster spend, duplicate tools, inactive seats, renewal dates, and owner approvals without another manual monthly clean-up exercise.
Teams dispute shared costs and renew tools nobody actively owns.
Namespace allocation, seat downgrade tasks, renewal evidence, and procurement-ready approval history.
Designed for the access objection.
Customers do not need to hand over broad write access. Siftlogiq starts read-only, stores secret references, minimizes data, and requires approval before execution.
Trust model in one view.
You can begin with billing, usage, inventory, repo metadata, prompts, tickets, and SaaS signals using least-privilege access.
Your secrets stay in your vault or provider trust boundary. Raw prompts and payloads stay redacted unless your policy allows them.
Your owners see expected saving, risk, blast radius, rollback, and implementation path before any write action.
Your changes can go through PR, Jira, GitOps, or narrow APIs instead of broad default write access.
Your audit trail keeps timestamp, actor, source, before/after impact, quality check, and rollback status.
Controls your security team can validate.
Pilot first. Expand after verified savings.
Start with a guided proof pilot, validate savings from a narrow read-only scope, then expand only after your security, finance, and engineering teams trust the evidence.
Secure Pilot
One source, read-only, prioritized savings queue, security review pack, and verified ledger sample.
Platform
Multi-source coverage, approval routing, savings ledger, dashboards, integrations, and governance controls.
Enterprise
Private deployment path, SSO/SCIM, SIEM export, custom retention, customer-managed keys, and support SLAs.
Watch the operating loop before starting the trial.
This guided tour shows the product experience without exposing the full trial console: connect read-only, see AI prompt savings, approve a safe fix, verify savings, and keep rollback ready.
Connect AWS, GitHub, OpenAI, and Jira.
Start with one safe source. Siftlogiq asks for only the connection fields needed, keeps secrets in the customer boundary, and shows value before write access.
- AWS role ARN and account IDs
- GitHub app installation and repo scope
- AI provider, gateway, workspace, or IDE usage source
- Jira project for approval records
Start with one source and one verified saving.
The trial is designed for customer trust: no broad write access, no raw payload capture, no black-box execution.
Your trial path.
You can start with one safe source, review a realistic remediation queue, and walk through approval, execution, verification, ledger, dashboard, security, and settings without granting broad write access.
| Step | Your action | What you see |
|---|---|---|
| Register | Create your workspace | A clean setup screen with no connected source yet |
| Connect | Select one source first | Only fields relevant to that platform are requested |
| Scan | Run a read-only scan | A prioritized savings queue appears |
| Approve | Allow one safe fix | A PR, Jira ticket, GitOps path, or scoped execution option is prepared |
| Verify | Review before/after | Your ledger records finance-ready proof |
Request a guided audit.
Share the minimum information needed for your secure, read-only audit. Your team can start with one source, one owner, and one verified saving before expanding access.
What happens after a team asks for trial access.
Keep the motion high-trust: buyers see enough to believe, then evaluate the full product in a controlled workspace.
Request a secure trial workspace.
The full trial console is shared after registration or a guided pilot conversation. That keeps the product protected while giving your team a safe, read-only evaluation path.