@meta
  v: 1
  route: /ai/saas/
  generated: 2026-09-19T03:52:00Z
  ttl: 1d

@intent
  purpose:    AI features inside your SaaS product plus automation for your operation: copilots, document intelligence, RAG, support triage, with cost controls built in.
  audience:   visitor, prospective-client, ai-agent
  capability: learn, assess, contact, call

@state
  business: Titanium Computing
  page: "AI Features for Your Product, Automation for Your Operation"
  phone: +1-512-623-9199
  address:
    street: "2013 Wells Branch Pkwy, Suite 310"
    city: Austin
    region: TX
    postal: 78728
  hours: 24/7
  practice_overview: /ai.agent
  practice: Titanium AI
  industry: SaaS
  engagement_shapes[3]: Feature Build, Embedded with your engineers, Operations automation
  models: "Anthropic, OpenAI, or open-weight models you host (swappable by design)"
  page_sections[5]:
    - Two Sides of the Same Engagement
    - Why SaaS Teams Build With Us
    - Three Ways to Engage
    - AI for SaaS FAQ
    - Ship the AI Feature. Keep the Margin.
  section_summaries[3]{section,summary}:
    Why SaaS Teams Build With Us,"We already run infrastructure, security, and compliance for SaaS companies, so the AI we build lands in an environment we understand end to end. No handoff gap between the team that builds the feature and the team that keeps it up at 2 AM."
    AI for SaaS FAQ,"Whichever fits the feature and your constraints: Anthropic, OpenAI, or open-weight models you host. We design so the model is swappable, because pricing and capability shift every quarter and your product shouldn't be hostage to one vendor."
    Ship the AI Feature. Keep the Margin.,Start with a one-hour assessment of your product roadmap and operation.
  two_sides_of_the_same_engagement[2]{category,title,detail}:
    IN YOUR PRODUCT,AI Features Your Customers Use,"Built to ship inside your existing architecture, with your engineers or as a standalone build."
    IN YOUR OPERATION,Automation That Protects Margin,Scale support and ops without scaling headcount at the same rate.
  two_sides_of_the_same_engagement_highlights[8]:
    - Assistants and copilots inside your app
    - "Document and data intelligence (summarize, extract, classify)"
    - Search and Q&A over your customers' data (RAG)
    - "Usage-safe design: cost controls, rate limits, tenancy isolation"
    - "AI-assisted support: triage, drafting, call QA"
    - Onboarding and back-office workflow automation
    - Internal knowledge systems for your team
    - The same triage system we run across 100+ MSP clients
  why_saas_teams_build_with_us_points[3]{title,detail}:
    One accountable partner,"Feature, infrastructure, security, and support under one roof."
    Compliance-aware builds,"SOC 2-minded data handling from the first commit, not retrofitted for the audit."
    Proof over pitch,Working AI call-QA and triage systems in production for real clients today.
  three_ways_to_engage[3]{category,title,detail}:
    FEATURE BUILD,We Ship the Feature,"A scoped AI feature designed, built, and delivered into your codebase: the assistant, the document intelligence, the search. Fixed scope, fixed price, your repo."
    EMBEDDED,We Work With Your Engineers,"Your team keeps ownership; we bring the AI experience they haven't had time to build: prompt architecture, eval harnesses, cost controls, and the production war stories."
    OPERATIONS,We Automate Your Back Office,"Support triage, onboarding, and internal knowledge systems for the operation behind the product, so headcount doesn't scale linearly with customers."
  faqs[4]{question,answer}:
    Which AI models do you build on?,"Whichever fits the feature and your constraints: Anthropic, OpenAI, or open-weight models you host. We design so the model is swappable, because pricing and capability shift every quarter and your product shouldn't be hostage to one vendor."
    How do you handle our customers' data?,"Tenancy isolation from the first design session: what data reaches the model, what gets logged, and zero-retention agreements with model vendors. If your customers demand it, features can run against a private model on your own infrastructure."
    Can you work inside our existing codebase?,"Yes. We work in your repo, your CI, and your review process. You keep the code, the keys, and the vendor relationships; nothing routes through infrastructure you don't control."
    What does an AI feature cost to run?,"Less than most teams fear, if it's designed for cost from day one. We model per-tenant token costs during scoping and instrument them in production, so you can price the feature knowing your margin instead of discovering it on the first invoice."

@actions
  - id: request_free_consultation
    method: GET
    href: /contact/
    inputs[1]{name,type,required}:
      need,string,false
  - id: call_titanium_computing
    method: GET
    href: tel:+15126239199
  - id: book_free_ai_readiness_assessment
    method: GET
    href: /free-consultation/?need=ai
  - id: view_pricing
    method: GET
    href: /pricing/
  - id: view_human_page
    method: GET
    href: /ai/saas/

@context
  > Your customers expect AI in the product, and your margins depend on a lean operation behind it. We build both, from the team that already manages infrastructure for SaaS companies.
  > AI features inside your SaaS product plus automation for your operation: copilots, document intelligence, RAG, support triage, with cost controls built in.
  > Titanium Computing is an engineer-run managed IT, cybersecurity, and compliance provider in Austin, TX, serving Central Texas since 2016. Flat per-user monthly pricing, no setup fees, and a named engineer who knows your network.

@nav
  self: /ai/saas.agent
  parents: [/.agent, /ai.agent]
  peers: [/ai.agent, /ai/advisory.agent, /ai/agentic-automation.agent, /ai/automotive.agent, /ai/accounting.agent, /ai/private-ai-appliance.agent, /ai/ainode.agent, /formflows.agent, /callscrub.agent, /case-studies.agent, /contact.agent]