AI & Automation
Agents that read,
decide, and act.
Not chat. Not slogans. The boring high-leverage AI: agents that process invoices, route tickets, summarize calls, watch your inbox, and only escalate when they actually need a human.
agent / accounts
The stack
Boring choices, executed well. Everything you’d pick if you were us.
Read documents.
Take the next action.
Invoices, contracts, support tickets, emails — agents that parse them, run validations, call your APIs, and finish the task. Not a chatbot you have to babysit.
- Tool-using agents with your APIs as tools
- Self-correcting on validation failures
- Human-in-the-loop on the cases that matter
Funnel · Q4
Conversion +47%
Pipelines that
run themselves.
Trigger → process → decide → act. Scheduled, event-driven, or webhook-fed. Idempotent and observable, so when it does break you know exactly where.
- Step-by-step traces in production
- Cost + latency budgets per run
- Rerunnable from any step
Workflow · accounts
4 steps · automated
Trigger
New invoice
Process
Parse + validate
Decide
AI categorize
Act
Sync to NetSuite
RAG that
actually answers.
Vector + lexical + structured query, evaluated on your actual data. Citations, freshness, source filters. The kind of retrieval where the answer comes with receipts.
- Hybrid retrieval (vector + BM25)
- Eval set + regression tests
- Citation links to source paragraphs
Files
- ▾ src
- index.ts
- api.ts
- db.ts
- ▾ lib
- queue.ts
- workers.ts
Token bills
that don't surprise.
Per-tenant cost dashboards. Rate limits. Output validation. Prompt-injection guards. The unglamorous work that keeps an AI feature from becoming an AI incident.
- Spend dashboard per customer / endpoint
- Output schema validation on every call
- Prompt-injection + PII tests in CI
Overview · 30d
Live dashboard
MRR
$48k
Active
12.4k
Churn
1.8%
What ships
Everything below,
every project.
No upsells, no “that’s out of scope.” If it’s on this list, it’s included in the base price.
Model selection
Claude / GPT / open-source — picked per task by cost, latency, and quality benchmarks.
Agent design
Tool-using agents with your APIs. Sane fallbacks when the model gets confused.
RAG pipeline
Document ingest, chunking, embeddings, hybrid retrieval, eval set.
Prompt engineering
Versioned prompts, A/B tests, regression suites. Not vibes-based.
Observability
Per-call traces, token spend, latency, output validation. Sentry + custom dashboards.
Safety guards
Prompt-injection mitigations, PII redaction, output schema validation.
Cost controls
Per-tenant budgets, rate limits, cache layers — so token bills stay predictable.
Eval framework
Continuous evals against your real data so quality regressions surface fast.
30-day support
Tuning + bug fixes free for 30 days. Then retainer or hourly.
AI Build
One flat price.
Scope written down.
For agents, RAG, content pipelines, classification, summarization, automation.
From
Fixed-scope engagement · 50/50 milestone billing
- Agents with tool use
- RAG + eval framework
- Observability + cost guards
- 3–5 week delivery
FAQ
Questions
we get every week.
Something more specific? Email hello@invokube.com — reply within hours.
AI that does the work,
not the demo.
Describe the workflow. We'll show you what's automatable in 48 hours.