TRENDS

Building vs. Buying AI: The Real Math for B2B SaaS

Agensphere TeamJanuary 14, 20257 min read

Your head of product says: "We need AI features to stay competitive."

Your CFO asks: "What's this going to cost?"

You have three options: build in-house, hire an agency, or buy SaaS tools. Each has wildly different costs, timelines, and outcomes.

Here's the real math, based on working with 20+ B2B SaaS companies over the past 18 months.

The Three Approaches

Option 1: Build In-House (Hire an AI Team)

What this looks like:

  • Hire 2-3 AI/ML engineers (full-time)
  • 3-6 months to build initial features
  • Ongoing iteration and maintenance

Option 2: Agency/Consultancy (Like Agensphere)

What this looks like:

  • Fixed scope project or retainer engagement
  • 6-12 weeks to production
  • Transfer code ownership, you maintain

Option 3: Buy Off-the-Shelf (SaaS Tools)

What this looks like:

  • Integrate third-party AI tools (chatbot platforms, AI APIs)
  • 1-4 weeks to integrate
  • Monthly subscription fees, no customization

Let's break down the real costs of each.

Option 1: In-House Team - The $500K+ Reality

Year 1 Costs:

Salaries:

  • Senior ML Engineer: $180K-250K
  • AI Product Manager: $150K-200K
  • Data Engineer (part-time): $80K-120K (50% allocation)
  • Total salaries: $410K-570K/year

Infrastructure:

  • GPU compute (AWS/GCP): $1K-$3K per month = $12K-$36K per year
  • Vector databases: $500-$2K per month = $6K-$24K per year
  • Monitoring/logging tools: $500 per month = $6K per year
  • Total infrastructure: $24K-$66K per year

Tooling & APIs:

  • OpenAI/Anthropic API credits: $2K-$10K per month = $24K-$120K per year
  • Fine-tuning costs: $5K-20K one-time
  • Development tools (IDEs, testing): $5K/year
  • Total tooling: $34K-145K/year

Hidden costs:

  • Recruiting fees (20% of salary): $82K-114K one-time
  • Onboarding time (3 months unproductive): $100K+ opportunity cost
  • Failed experiments (expected): $50K+ in wasted compute/time
  • Total hidden: $232K+ one-time

Grand total Year 1: $700K-1M+

Timeline to production: 6-12 months (includes hiring, onboarding, building)

When This Makes Sense

You should build in-house if:

  • AI is your core product (e.g., you're building an AI-native SaaS)
  • You need ongoing model research (not just integration)
  • You plan to hire 5+ AI engineers eventually
  • You have $5M+ in funding or revenue

Example companies:

  • Midjourney (AI image generation = core product)
  • Jasper (AI writing = core product)
  • Perplexity (AI search = core product)

You should NOT build in-house if:

  • AI is a feature, not the product
  • You need production features in less than 6 months
  • Your engineering team is under 20 people
  • Budget is constrained

Option 2: Agency Build - The $40K-100K Range

Typical engagement costs (using Agensphere as example):

Tier 1: Intelligence Integration ($15K-28K/month, 2-3 month engagement)

  • Integrate AI into existing product
  • Build RAG systems, embeddings pipelines
  • Total: $30K-84K

Tier 2: Custom Intelligence Layer ($28K-45K/month, 2-4 month engagement)

  • Multi-agent systems
  • Custom model training
  • Full architecture design
  • Total: $56K-180K

Tier 3: Enterprise AI Systems ($45K+/month, 4-6 month engagement)

  • Company-wide AI infrastructure
  • Total: $180K-270K+

What you get:

  • Dedicated team (2-4 engineers)
  • Production-ready code in 6-12 weeks
  • Complete code ownership (you keep everything)
  • Optional ongoing support (separate retainer)

Hidden costs:

  • Your team's time (product manager, engineer for handoff): $10K-$20K equivalent
  • Ongoing API costs (if using OpenAI/Anthropic): $500-$5K per month
  • Infrastructure hosting: $100-$1K per month

Grand total: $50K-$200K one-time + $600-$6K per month ongoing

Timeline to production: 6-12 weeks

When This Makes Sense

You should use an agency if:

  • You need production-ready AI features in 2-3 months
  • You don't want to hire a full AI team
  • You want to own the code (not depend on SaaS)
  • Budget is $50K-200K for initial build

Example use cases:

  • SaaS adding AI-powered search
  • B2B platform adding intelligent recommendations
  • Customer support tool adding AI triage
  • Internal tool for AI-assisted workflows

You should NOT use an agency if:

  • You need ongoing model research (agencies build, don't research)
  • Your budget is under $30K
  • You're okay with SaaS vendor lock-in
  • You need something off-the-shelf (no customization)

Option 3: SaaS Tools - The $500-$5K Per Month Trap

Common AI SaaS tools:

  • Chatbot platforms (Intercom, Drift AI): $500-$2K per month
  • AI search (Algolia AI, Elasticsearch): $1K-$5K per month
  • Document AI (DocuSign AI, Adobe): $500-$3K per month
  • Customer support AI (Zendesk AI, Freshdesk): $1K-$3K per month

Year 1 costs:

Subscriptions:

  • Primary tool: $1K-$5K per month = $12K-$60K per year
  • Additional seats/usage: $500-$2K per month = $6K-$24K per year
  • Total subscriptions: $18K-$84K per year

Integration work:

  • Engineering time to integrate: $10K-$30K one-time
  • Custom API work (if needed): $5K-$15K

Hidden costs:

  • Usage overages (message limits, API calls): $2K-$10K per year
  • Vendor lock-in (switching costs if you leave): $20K-$50K
  • Feature limitations (can't customize beyond what vendor offers): Opportunity cost

Grand total Year 1: $35K-140K

Timeline to production: 1-4 weeks

When This Makes Sense

You should use SaaS tools if:

  • You need something live in less than 1 month
  • Your use case is standard (common chatbot, basic AI search)
  • You're okay with vendor limitations
  • Budget is under $50K
  • You don't care about code ownership

Example use cases:

  • Basic customer support chatbot
  • Simple document search
  • AI email drafting for sales team
  • Internal FAQ bot

You should NOT use SaaS if:

  • Your use case requires customization
  • You're worried about vendor lock-in
  • You need to control costs at scale (usage-based pricing explodes)
  • Data privacy/compliance is critical

The Hidden Costs Everyone Misses

Opportunity Cost of Speed

Scenario: Your competitor ships AI features 6 months before you.

Cost: Lost market share, customers choosing them, harder sales cycles.

Math: If AI features increase conversion by 10%, and you close $500K/year in new business, 6 months delay = $25K-50K lost revenue.

Who wins on speed:

  • SaaS tools: 1-4 weeks (fastest)
  • Agency: 6-12 weeks
  • In-house: 6-12 months (slowest)

Maintenance and Iteration

Year 2+ costs:

In-house:

  • Salaries continue: $410K-570K/year
  • Infrastructure: $24K-66K/year
  • Iteration budget: $50K-100K/year
  • Total: $484K-736K/year ongoing

Agency:

  • Optional retainer: $10K-30K/month = $120K-360K/year
  • Or: DIY maintenance with your team: $50K-100K/year
  • Total: $50K-360K/year (you choose)

SaaS:

  • Subscriptions: $18K-84K/year (same as Year 1)
  • Overages increase as you scale: +$10K-30K/year
  • Total: $28K-114K/year (but no control over pricing)

Flexibility and Ownership

What happens when your needs change?

In-house:

  • Full control: Pivot freely
  • Cost: Existing team can adapt

Agency:

  • You own the code: Modify yourself or hire agency again
  • Cost: $0 if DIY, $10K-50K if agency helps

SaaS:

  • Vendor lock-in: Can't customize beyond API limits
  • Cost: Switch to new vendor ($20K-50K migration) or build from scratch

Real-World Comparison: Same Feature, Three Approaches

Let's compare building AI-powered customer support triage (routes tickets to right team, suggests answers).

Approach 1: In-House

Timeline: 9 months (3 months hiring, 6 months building)

Cost:

  • Year 1: $750K (salaries + infrastructure)
  • Year 2: $550K (ongoing team)
  • Total 2-year: $1.3M

Outcome: Fully custom system, exactly what you want, ongoing iteration

Approach 2: Agency (Agensphere Tier 1)

Timeline: 10 weeks

Cost:

  • Build: $60K (3 months @ $20K/month)
  • Ongoing: $50K/year (your team maintains)
  • Total 2-year: $160K

Outcome: Production-ready system, you own code, moderate customization

Approach 3: Zendesk AI Add-On

Timeline: 2 weeks

Cost:

  • Year 1: $36K ($3K/month subscription)
  • Year 2: $42K (price increase + overages)
  • Total 2-year: $78K

Outcome: Working system quickly, limited customization, vendor dependency

Which wins?

  • Cheapest 2-year cost: Zendesk ($78K)
  • Best customization: In-house ($1.3M)
  • Best value: Agency ($160K) - Balance of custom + cost + speed

Our Recommendation: The Staged Approach

Most B2B SaaS companies should follow this path:

Stage 1: Validate with SaaS (Months 1-3)

Goal: Prove AI features drive value

Action: Use off-the-shelf tools (Intercom AI, Algolia, etc.)

Cost: $5K-15K

Outcome: Learn what users actually want, validate hypothesis

Stage 2: Build Custom (Months 4-6)

Goal: Own your AI stack, optimize costs

Action: Hire agency to build production system

Cost: $50K-150K

Outcome: Custom system, code ownership, no vendor lock-in

Stage 3: Hire In-House (Year 2+)

Goal: Continuous innovation, research capabilities

Action: Hire 1-2 AI engineers to iterate on agency-built foundation

Cost: $200K-400K/year

Outcome: In-house team building on proven foundation (not starting from scratch)

Why this works:

  • Avoid wasting 6 months building wrong thing
  • Validate before big investment
  • Agency accelerates you past MVP stage
  • In-house team has working codebase to start from

Decision Framework: Which Option For You?

Answer these questions:

1. What's your timeline?

  • Need production in less than 1 month → SaaS
  • Need production in 2-3 months → Agency
  • Timeline flexible (6+ months) → In-house

2. What's your budget?

  • Less than $30K → SaaS
  • $30K-200K → Agency
  • $200K+ → In-house or Agency

3. How custom is your use case?

  • Standard (chatbot, search) → SaaS
  • Moderately custom (tailored workflows) → Agency
  • Highly custom (novel AI research) → In-house

4. Do you want to own the code?

  • No (okay with vendor) → SaaS
  • Yes (but don't want to maintain) → Agency initially, then decide
  • Yes (and want full control) → Agency or In-house

5. How critical is AI to your product?

  • Nice-to-have feature → SaaS
  • Competitive differentiator → Agency
  • Core product value → In-house

How Agensphere Fits In

We're the agency option, optimized for B2B SaaS companies who:

  • Need production AI in 6-12 weeks (not 6-12 months)
  • Want to own the code (not rent from SaaS)
  • Don't want to hire a full AI team yet
  • Budget $50K-200K for initial build

What makes us different:

  • Complete ownership: You keep all code, no licensing fees
  • Production focus: We build systems that ship, not research projects
  • Fixed timeline: 2-week guarantee on prototypes
  • No lock-in: After handoff, you can maintain or hire us for ongoing work

Pricing:

  • Tier 1: $15K-28K/month (2-3 month engagements)
  • Tier 2: $28K-45K/month (2-4 month engagements)
  • Tier 3: $45K+/month (enterprise)

See full pricing and scope


Not sure which approach makes sense for your use case? Let's talk and we'll help you decide (even if that means recommending a SaaS tool over working with us).

Questions about build vs. buy? Email hello@agensphere.com

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