Build vs buy
Build your own AI sales stack, or buy one that works today?
Your engineers can wire an LLM to your CRM in a sprint. The hard part is everything after: pipelines, prompts, evals, edge cases, and maintenance that never ends. Airspeed ships that work as a product.
- Live in weeks, not quarters
- From $5K per year, no engineering headcount
- A RevOps analyst on the build
A 30-minute demo and expert Q&A.
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The honest comparison
Both paths get you AI on your calls. They differ in when it works, what it costs, and who carries it.
What the build actually involves
The demo takes a weekend. Production takes a team. Here is the work between the two.
Wire up the data
Call recordings, emails, CRM objects, and tickets, all normalized into one pipeline before a single prompt runs.
Build the integrations
Salesforce or HubSpot writes, calendar and email access, permissions, and rate limits. This is where most internal builds stall.
Tune the prompts
Every sales motion is different. Someone has to iterate on prompts against real calls, then do it again when the model changes.
Evaluate the outputs
Without an eval harness you find out about bad CRM writes from angry reps. Building one is a project in itself.
Handle the edge cases
Multi-language calls, reassigned deals, merged accounts, reps who go off script. The long tail never ends.
Maintain it forever
Model deprecations, API changes, new use cases from sales leadership. The build is never done, so the team never leaves.
What you get on day one
Everything the internal build was going to deliver in a year, working in your first month.
One brain, every conversation
Every call, email, and ticket lands in a single model of your buyer. No pipelines to design, no data warehouse project first.
CRM that updates itself
Airspeed writes to Salesforce and HubSpot after every call. Fields, notes, next steps. No rep login, no custom integration to own.
Agents that act
Stalled deal spotted, re-engagement drafted. Closed-won pattern found, outbound launched. The work finishes itself.
Why teams buy instead
Not because they could not build it. Because the second year of owning it is worse than the first.
Weeks to live, not quarters
A forward-deployed RevOps analyst tunes Airspeed to how you sell. Foleon hit payback in under two months.
A subscription, not a headcount plan
Airspeed starts at $5K per year. One AI engineer costs more than that per week, before infra and eval tooling.
It compounds without your roadmap
Airspeed improves across 100s of revenue teams. Your internal build only improves when your engineers get back to it.
Your engineers stay on your product
The build pulls senior engineers into GTM tooling for a year. Buying keeps them on the thing your customers pay for.
Skip the build.
Keep the outcome.
See Airspeed log the call, update your CRM, and draft the follow-up, in your own pipeline.
When does building in-house make sense?
When GTM tooling is your product, or you have a dedicated ML platform team with spare capacity and an eval culture. For most revenue teams, the maintenance cost outlasts the excitement.
We already started building. Is it too late to switch?
No. Most teams we work with tried an internal prototype first. Airspeed runs alongside it during the trial, so you can compare outputs on your own calls before deciding.
What does Airspeed cost?
Plans start at $5K per year. Pricing scales with team size, and every plan includes the forward-deployed RevOps analyst.