What does this cost and what do we keep?
Engagement & Cost
What each engagement costs, what is included, how it compares, and what happens when it ends.
How much does VGL Studio cost?
AI Managed Pipeline runs $2,500 to $5,000 per month depending on ICP complexity and team scope. AI Build Lab runs $2,000 to $5,000 per month across a two to three month focused build sprint, so a complete sprint totals between $4,000 and $15,000. Neither requires a long-term contract, and both include the strategy work rather than billing it as a separate engagement.
Why it matters
Where an engagement lands in its range depends on scope rather than negotiation. A single vertical with one persona sits at the bottom. Multiple verticals, multiple personas and a larger internal team to coordinate with sits at the top.
Strategy being included is not a discount. It is a requirement, because an engine governed by an undefined ICP produces activity.
What to look at
- ICP complexity and number of personas
- How many internal stakeholders coordinate
- Whether existing systems need integration
Worked example: what changes the number
A software company selling one product to operations leaders in one vertical sits near the bottom of the range. One ICP, one persona, one message, one sequence pair. Roughly $2,500.
A services firm selling to three verticals, each with a different buyer and a different reason to care, needs three ICP definitions, three message sets and three sequence pairs, plus coordination with an internal marketing team who own the brand voice. That sits near $5,000.
The variable is almost never volume of contacts. It is the number of distinct arguments the engine has to make, because each one needs its own definition, its own proof and its own sequencing.
A way to estimate before a call: count the sentences you would need to explain who you help, and notice how many start with a different kind of company. One sentence sits at the bottom of the range. Three sit at the top. If you cannot get it under four, the honest answer is that positioning work has to happen before the engine does, and that is a different engagement at a different price. We would rather say that on the first call than discover it in month two.
One more variable nobody expects: how much of your existing pipeline data is usable. A CRM with two years of clean outcome history shortens the ICP work considerably. A CRM full of stale records adds a week before anything can be scored.
The VGL perspective
We publish the numbers because the alternative is a discovery call whose main purpose is finding out what you will pay. That is a worse experience and it selects for the wrong clients.
What does it cost to build a GTM engine in-house?
Roughly $12,000 to $18,600 a month once you count a data platform at $1,250 to $2,500, a CRM at $1,000 to $3,000, outbound tooling at $300 to $600, one loaded SDR at $7,500 to $9,000, and RevOps capacity at $2,000 to $3,500 to connect and maintain it. That figure excludes recruiting cost and the three to six months before a new hire produces a first qualified conversation.
Why it matters
The time cost is the part most models leave out and it is frequently larger than the spend. Six months of no pipeline from a seat you are already paying for is six months of runway.
It also assumes the SDR works out. Replacement restarts the clock on both the ramp and the recruiting cost.
What to look at
- Five separate line items, not one
- Ramp time before any pipeline
- Recruiting and replacement risk
Worked example: a 40-person B2B software company
Say you decide to build it. You license a data platform at $1,800 a month, add a CRM at $1,500, outbound sequencing at $450, and hire one SDR at $85,000 base plus commission, which lands around $8,200 a month fully loaded. Your head of ops absorbs the RevOps work at roughly a quarter of their time, call it $2,600. That is $14,550 a month.
Now add the timeline. Recruiting takes six weeks. Onboarding and ramp take another twelve before the seat produces a qualified conversation. So months one through four cost roughly $58,000 and return nothing, and that assumes the hire works out on the first attempt.
The same four months of a managed engagement at $4,000 runs $16,000 and produces first conversations in week three or four. The gap is not primarily the monthly rate. It is that one path has a four month hole at the front of it.
There is a second-order effect worth pricing. The in-house path concentrates the capability in one person, so a resignation restarts both the recruiting clock and the ramp. The managed path concentrates it in a system and a documented ICP, which transfers. Neither is universally correct. A company with an existing RevOps function and a proven motion should probably hire, because ramp risk is lower and the seat is the only real cost. A company with neither is buying the ramp risk as well as the seat, and usually has not priced it.
The VGL perspective
We built this comparison because our own cost claim was unfalsifiable without it. A percentage with no line items underneath it is an assertion, and buyers are right to discount those.
Is there a long-term contract?
No. Both engagements run on simple terms with no long-term commitment required. A build sprint is naturally bounded at two to three months because it is scoped to a single system rather than an open programme. Managed pipeline continues month to month for as long as it keeps producing, which is the arrangement that points the incentive at outcomes rather than at renewal dates. Either can be stopped without penalty, and you keep everything either way.
Why it matters
Annual contracts exist to protect the vendor from underperformance. Month to month means the engine has to keep earning the next month, which is the correct pressure for us to be under.
It also changes what gets reported. Activity reporting is what you send when the contract is signed for a year.
What to look at
- Month to month, no minimum term
- Build sprints bounded by scope
- Reporting measured on pipeline created
The VGL perspective
Engagements should continue because something proved out, not because a term sheet required it. That principle costs us revenue occasionally and we would still make the same trade.
What happens to our data if we stop?
You keep everything. Contacts, sequence history, CRM infrastructure and any system built during a sprint are yours throughout the engagement and after it ends. Nothing is withheld at exit and nothing is licensed back to you. This is the clearest structural difference from most agency arrangements, and it is worth asking about explicitly before signing anything with anyone, in writing rather than in principle. The answer should take one sentence.
Why it matters
Many arrangements retain the contact database and the sequence history, which turns leaving into a loss of the asset you spent a year building. That is a switching cost wearing the costume of a service term.
Data ownership also means the engine keeps working if you bring it in-house later. We treat that as a feature rather than a risk.
What to look at
- Contacts and sequence history transfer
- CRM infrastructure is yours
- Built systems transfer at handover
The VGL perspective
If a partner cannot answer this question in one sentence, that is the answer. We made it one sentence deliberately.
Can both solutions run at the same time?
Yes, though it is rarely the right first move. Most engagements start with one, prove it, then expand. When both do run together the usual sequence is managed pipeline first, because conversations create both the urgency and the data that make the right build obvious. Build work then produces the buyer-facing applications that feed the top of that same funnel.
Why it matters
Running both from day one doubles the surface area before either has proven out, which makes it considerably harder to tell what worked.
Sequencing them means the second engagement is informed by evidence from the first rather than by a guess made at the same time.
What to look at
- One engagement, proven, then expanded
- Pipeline usually first
- Build work informed by what pipeline surfaced
The VGL perspective
Win first, then scale applies to buying us as much as to anything else. We would rather start smaller than sell more.
Related insights
Long-form on this topic
Insight pieces expanding on these answers publish twice a month from October 2026. They will appear here as they go live.
First pieces publishing October 2026. In the meantime, the four concepts set out the thinking these answers are built on.
Start here
Find out where your own growth engine stands
The AI Growth Readiness check takes about three minutes. It scores you across six dimensions, places you on the growth maturity model, and gives a recommendation you can act on, including when the honest answer is not yet.
What you get back
- A score across growth dependency, unit economics and systems
- Your position on the growth maturity model
- A recommendation, or an honest not yet
- A concrete next step either way