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SwankyForge
SwankyForge
Pricing

How much would this cost?

Pick a starting point, then adjust the team and hours.

Starting point
Complexity
Pace
Estimated project

Estimated cost $14,500

310 hours across 5 roles · blended $47/h

Delivery
5–7 weeks
Risk
low

Well-understood problem shape. We have shipped this pattern before.

Rates are blended day-one rates for a dedicated pod, billed monthly. Fixed-price is available once scope is frozen.

See what we shipped for these numbers
Typical projects

Benchmark projects, with prices.

Bands from a focused build to a multi-source one.

Internal AI Copilot

Loaded
  • RAG
  • Search
  • Citations
  • Tool calling
Price
$8k $18k
Duration
4–8 weeks

Baseline complexity: Standard

Read the case

Recommendation System

  • Retrieval
  • Ranking
  • Personalization
  • A/B testing
Price
$14k $42k
Duration
2–4 months

Baseline complexity: Standard

Demand Forecasting

  • Time series
  • Backtesting
  • Hierarchies
  • Capacity planning
Price
$10k $28k
Duration
1–3 months

Baseline complexity: Standard

Read the case

Computer Vision QA

  • Detection
  • Segmentation
  • Edge inference
  • Review loop
Price
$18k $56k
Duration
2–6 months

Baseline complexity: Complex

Agentic Workflow

  • Planning
  • Tool calling
  • Guardrails
  • Evaluation
Price
$13k $38k
Duration
6–12 weeks

Baseline complexity: Complex

FAQ

Straight answers.

The questions we get before a first call.

How do you price the work?

Hourly rates by role, quoted from a template. Fixed-price is available once discovery is done and scope is frozen.

How long do projects take?

Most production systems land in 4–16 weeks. The calculator on /pricing gives a range from the same model we use internally.

Who owns the IP and the models?

You do. Full transfer of code, weights, documentation and runbooks.

How do you handle sensitive data?

Least-privilege access, isolated environments, and no training on your data for anyone else. We will work inside your VPC when that is the constraint.

Prefer to talk first?

Send the outcome. We will say if ML is the right spend.

Talk to the engineers