Build vs. Buy

Stop renting your roadmap. Agents let you build the exact slice you need - faster than a vendor can add it - and own the change velocity.

Stop renting your roadmap. In one week, prototype the in‑house slice that replaces the 20% you actually use - complete with TCO, migration plan, and a path to production.

Book Prototype in the RoomRun the payback math

POV: Build vs. Buy just changed.

Agents turn the 20% you actually use into a thin, ownable system - with lower run‑rate, faster change, and clean integrations.

Taglines to test

  • Buy less. Build smarter.
  • Keep the value. Lose the markup.
  • From seats to sovereignty.
  • Replace SaaS, not your process.
  • Own your core. Own your margin.
  • The “SaaS tax” ends here.

Executive narrative

For a decade, “buy” beat “build” because packaged software shipped features and UI faster than small teams could. Agents flipped that trade‑off. Today, a tiny team can compose reliable workflows - retrieval, tools, evaluations, and human approvals - around your data model in days. You keep exactly the capabilities you need, integrate cleanly, and move at your own pace. The question isn’t “Can we build the whole product?” It’s “Should we own the 20% that drives our margin?”

Five reasons “build” wins more often (now)

  • Economics: Swap perpetual seat bloat for a small internal run‑rate. (CFO: lower TCO, shorter payback.)
  • Change velocity: Release weekly, not on someone else’s roadmap. (CIO: faster iteration without re‑platform risk.)
  • Integration fit: Native to your identity, data, and controls. (Ops: fewer brittle workarounds.)
  • Data & leverage: Easy exports, transparent logic, no black boxes. (Security: auditable, least‑privilege.)
  • Right‑sized UX: Thin UIs for operators; agents for the heavy lifting. (Product: more outcome per sprint.)

Build vs. Buy vs. Blend (the new default)

  • Build: The 20% you use constantly (and need to change often).
  • Buy: Regulated/commodity areas (payroll, tax, payments).
  • Blend: Keep a minimal vendor core; wrap your unique flows with agents.

Your flagship offer, Prototype in the Room, becomes the decision engine for all three paths.

Agentability Scorecard

Score 1–5 (low → high). ≥ 26 → build/prototype candidate.

  • Usage Concentration: Small subset of features drive most value
  • Change Frequency: Needs tweaks monthly/weekly
  • Integration Pain: Current tool fights your data model
  • Data Gravity: Your data already lives in your stack
  • Compliance Fit: Residency/controls the vendor can’t meet
  • UI Complexity Needed: Thin UIs + checklists are sufficient
  • Risk of Downtime: Vendor outages hurt; you need fail‑open options
  • Internal Talent: You can staff 0.2–0.5 FTE to own it (or retain us)

Use this score live in Prototype in the Room to prioritize the slice you’ll prototype.

Agentability factors
Mode
Legend & examples
Usage concentration
3
Change frequency
3
Integration pain
3
Data gravity
3
Compliance fit
3
UI complexity needed
3
Risk of downtime
3
Internal talent
3
Reporting quality
3
Results
Total
27 / 45
Percent
60%
026 (threshold)45
Prototype candidate

Green‑light Prototype in the Room to ship a thin, working slice in 1–5 days (or choose the 1‑week MVP‑Starter).

Top drivers to target first
  • Usage concentrationCut the 80/20 slice and ship a thin end‑to‑end prototype.
  • Change frequencyHigh change velocity favors owning the slice; build to keep iteration in your control.
  • Integration painMap data flows and wrap brittle vendor APIs; prioritize the worst friction first.
Recommended next step
Prototype in the Room
Ship a thin, working slice in 1–5 days (or a 1‑week MVP‑Starter).
Also consider
  • Replace Your SaaS
    Stand up an owned agentic workflow where vendor pain is highest.
    Integration pain + internal data gravity (or SaaS replacement mode) indicate an owned workflow is viable.
  • Prototype to Production
    Harden: integrations, guardrails, evals, observability, rollback.
    Risk/operability signals—add guardrails, evals, observability, and rollback patterns early.
Legend & examples

What each factor measures and how to score it. Use the 1/3/5 anchors to calibrate your inputs.

Usage concentration
Measures: How concentrated the workflow is among a small set of roles/steps.
Score 1
Spread across many roles/flows; low repetition per user.
Score 3
Team-level repetition; some variance between users.
Score 5
Highly concentrated in one role/flow; same steps daily.
Examples
  • Tier-1 support macro used by 8 reps 50+ times/day.
  • AP invoice triage done by 2 specialists.
Change frequency
Measures: How often the workflow or business rules change.
Score 1
Rarely changes (quarterly+).
Score 3
Monthly tweaks; occasional rule updates.
Score 5
Weekly/daily changes; product/ops move fast.
Examples
  • New SKUs weekly; promos rotate daily.
  • Pricing rules adjusted every sprint.
Integration pain
Measures: Friction with vendor APIs, auth, rate limits, or brittle connectors.
Score 1
Stable vendor; low maintenance.
Score 3
Some manual workarounds; occasional outages.
Score 5
Frequent breakages, rate limits, or missing endpoints.
Examples
  • CSV uploads for core data.
  • Vendor webhook limits throttle ops.
Data gravity
Measures: How much critical data lives inside your boundary (DWH, lakehouse, systems).
Score 1
Mostly external/vendor data.
Score 3
Mixed; some key tables internal.
Score 5
Core entities/tables internal and well-modeled.
Examples
  • Customer 360 in warehouse; service logs centralized.
  • Internal feature store exists.
Compliance fit
Measures: Ability to meet policy/regulatory needs (PII, audit, approvals).
Score 1
Heavy restrictions; unclear path.
Score 3
Manageable with controls/approvals.
Score 5
Clear policies; audit/approval patterns established.
Examples
  • SOX controls defined; approval matrix exists.
  • PII redaction policies enforced.
UI complexity needed
Measures: How thin the UI can be (agent-first with minimal shell vs. heavy bespoke UI).
Score 1
Rich custom UI required; many edge cases.
Score 3
Moderate forms/tables.
Score 5
Checklist-style; minimal inputs/outputs.
Examples
  • Two-field intake + checklist.
  • Single-page “approve/deny with note”.
Risk of downtime
Measures: Business impact from vendor downtime and ability to fail open/safe.
Score 1
Low impact; manual fallback is fine.
Score 3
Moderate impact; some SLAs.
Score 5
High impact; strong need for control/rollback.
Examples
  • Missed SLAs when vendor throttles.
  • Revenue loss if queue stalls.
Internal talent
Measures: Capacity/skills to build and operate an agentic slice.
Score 1
No bandwidth/skills today.
Score 3
Some experience; needs guidance.
Score 5
Strong builder/operator bench.
Examples
  • 1–2 builders w/ tool-calling experience.
  • On-call rotation + observability in place.
Reporting quality
Measures: Depth of analytics & observability: event instrumentation, consistent metrics, dashboards, agent evals.
Score 1
Manual spreadsheets; ad-hoc queries; little logging.
Score 3
Some dashboards/logs; inconsistent metric definitions.
Score 5
Well-instrumented events; consistent metrics; dashboards tracked; eval harness exists.
Examples
  • Events with user/session IDs; Looker/Mode dashboards reviewed weekly.
  • Agent eval suites (golden sets, A/B) and alerting wired.
Assumptions & Notes
  • Higher scores mean stronger fit for a build/prototype with agents.
  • Default pass bar is 26/45. Adjust to tune your bar.
  • Use alongside the Buy vs Build ROI Calculator to combine qualitative and financial signals.
  • Run this live in Prototype in the Room to select a thin vertical slice for the spike.

Simple ROI / payback math

Baseline SaaS spend (B) = seats × price/seat × 12 + overages
Internal run‑rate (R) = infra + (maintenance FTE × loaded cost)
Build cost (C) = days × blended rate
Payback (months) = C ÷ (B − R)
3‑yr NPV = discounted Σ(B − R) − C

Rule of thumb: If payback < 12 months and the scorecard ≥ 26, green‑light a prototype.

Run the numbers

Buy vs Build ROI Calculator

Compare the total cost of a SaaS subscription (buy) vs building in‑house (build). Adjust inputs to see payback, NPV, IRR, and savings.

Buy (SaaS)

$
$
$

Time/contractor costs to administer the SaaS

Baseline SaaS (B)$75,000
Buy TCO (B + admin)$85,000

Build (in‑house)

$

Fractional FTE to maintain feature parity

$
$
Run‑rate (R)$20,000
Build cost (C)$25,000

Financial Settings

Used for NPV and IRR calculations

Results

Annual savings (B + admin − R)$65,000
Monthly savings$5,417
Payback4 mos, 19 days
3-yr NPV$136,645
3-yr undiscounted net$170,000
3-yr ROI (undisc.)680.0%
IRR (3 yrs)254.15%
Discount rate used10.00%

Assumptions & Notes

  • Baseline SaaS B = seats × price/seat × 12 + overages.
  • Buy TCO includes your annual admin/ops cost for the SaaS.
  • Run‑rate R = infra + (maintenance FTE × loaded cost).
  • Build cost C = days × blended rate (one‑time at t=0).
  • Payback (months) = 12 × C ÷ (Buy TCO − R). If savings ≤ 0, there’s no payback.
  • NPV/IRR use annual cashflows: −C at t=0; +Savings at t=1..N.
  • Results are directional and exclude taxes, risk adjustments, and scope creep.

Objections → crisp responses

  • “We don’t have dev capacity.” – We deliver a runnable slice + backlog. Either we build MVP, or your team finishes with our docs/tests - headcount‑neutral to start.
  • “Will we rebuild a complex product?” – No. We build the smallest slice that fits your model and drop the rest. Monolith → mosaic.
  • “Security/compliance?” – Read‑only credentials for discovery, “ask‑to‑act” gates for writes, RBAC & audit from week one.
  • “What if the vendor catches up?” – You still win: the capability map + prototype gives leverage at renewal. Keep the slice, or negotiate from strength.

How the decision works (4 steps)

  1. Map capabilities → 2) Prototype slice → 3) TCO/Payback → 4) Decide: Build • Buy • Blend

Why this wins now

Cards to highlight: Economics • Change velocity • Integration fit • Data leverage • Right‑sized UX

Marketing & SEO engine

  • Agents continuously monitor search trends, social signals, and analytics to spot breakout opportunities.
  • Bulk generation pipeline (content + images) lets you target niches fast and publish static pages with clean JSON‑LD for SEO.
  • Automated validation ensures quality (duplication, relevance, safety) before publish.
  • Feedback loops tweak prompts, keywords, and internal linking based on real performance.

Proof & governance

  • Add 2–3 projects or before/after diagrams
  • Security & governance: RBAC, audit, redaction, approvals
  • Two paths: We build MVP • You build (handoff package)

CTA: Book a Prototype in the RoomContact us

Buy vs Build ROI Calculator

Compare the total cost of a SaaS subscription (buy) vs building in‑house (build). Adjust inputs to see payback, NPV, IRR, and savings.

Buy (SaaS)

$
$
$

Time/contractor costs to administer the SaaS

Baseline SaaS (B)$75,000
Buy TCO (B + admin)$85,000

Build (in‑house)

$

Fractional FTE to maintain feature parity

$
$
Run‑rate (R)$20,000
Build cost (C)$25,000

Financial Settings

Used for NPV and IRR calculations

Results

Annual savings (B + admin − R)$65,000
Monthly savings$5,417
Payback4 mos, 19 days
3-yr NPV$136,645
3-yr undiscounted net$170,000
3-yr ROI (undisc.)680.0%
IRR (3 yrs)254.15%
Discount rate used10.00%

Assumptions & Notes

  • Baseline SaaS B = seats × price/seat × 12 + overages.
  • Buy TCO includes your annual admin/ops cost for the SaaS.
  • Run‑rate R = infra + (maintenance FTE × loaded cost).
  • Build cost C = days × blended rate (one‑time at t=0).
  • Payback (months) = 12 × C ÷ (Buy TCO − R). If savings ≤ 0, there’s no payback.
  • NPV/IRR use annual cashflows: −C at t=0; +Savings at t=1..N.
  • Results are directional and exclude taxes, risk adjustments, and scope creep.