Services
AI for GTM & Finance
A data foundation for go-to-market and finance, then the agents that run the recurring work on top of it.
How we see the problem
Even with AI inside of vendors, manual processes and data hygiene are still issues.
The activity is already in the warehouse, the CRM, the ERP, billing, and the ledger. It does not reconcile, so a chat assistant drafts one step and people still pull the data, check the numbers, and chase the follow-ups.
The record does not reconcile
The CRM, the ERP, billing, and the ledger each hold a different version of the account.
Numbers have to tie out
Variance, cash, and the board pack still get rebuilt from exports finance can’t trace.
Customers see the output
Quotes, credits, and collection notes need a person’s sign-off before they go.
Each workflow starts from scratch
A prompt for one job never becomes the context the next agent, in revenue or finance, uses.
What it runs on
Revenue and finance agents read one account record.
We build the math and the approvals on that record once. The next agent reads them.
- 01
Data foundation
CRM, ERP, product, support, billing, and the ledger in one model, with accounts, invoices, and events on the right record. A managed warehouse, or the one you already run, written back to Salesforce, HubSpot, and the books.
- 02
Intelligence
Health, risk, and forecast signals for revenue, and the same math for variance, cash, and the board pack. A person can open any figure and see the source.
- 03
Agent operating layer
Every agent starts from those facts. Prompts, tools, and approvals live in one loop, and each run keeps its reasoning, tool calls, handoff, and outcome.
Where we start
Agents for go-to-market and finance.
Go-to-market and finance agents start from the same account record, and a person signs off on quotes, credits, collection notes, and any figure that has to match the ledger.
Go to market
- 01
Pipeline Hygiene
Missing fields, stale stages, and account gaps, caught before they distort the forecast. It reads the shared account record and routes the gaps for a person to fix.
- 02
Deal Risk
Pipeline risk while there is still time to act, with the drivers named. The signal comes from product, activity, and stage history.
- 03
Renewal Risk
Upcoming ARR flagged before the renewal window becomes a fire drill. The agent names the drivers, drafts the next step, and routes it to the owner.
- 04
Expansion
Usage, fit, and timing turned into an account-level growth play. It names why now, and routes the play to the owner.
- 05
Forecast
One forecast from product, pipeline, billing, and the ledger. Revenue and finance review the same number, and every figure traces to its source.
- 06
Executive Briefing
Account, forecast, and board briefs for leadership, each figure tied to its source. The brief stops for review before it goes out.
Finance
- 01
Variance
What moved against the plan, in the words finance will send. Every line traces to the ledger.
- 02
Cash
Cash scenarios from billing, collections, and the ledger, with the assumptions named.
- 03
Reconciliation
Invoices matched to the ledger, and vendor spend reviewed. Exceptions route to a person.
- 04
Collections
Follow-ups on open invoices, drafted from billing. Nothing goes to a customer until someone signs off.
On the same foundation: Onboarding, Customer Health, and Next Best Action. Marketing uses it for campaign briefs and weekly performance summaries.
Built on AgentFlow, the harness behind our production agents, and yours to own once it’s handed over. For work outside GTM and finance, see Custom Agent and App Development.
How the work runs
Ship one agent. Add the next once it runs every day.
- 01Pick the job
A renewal, a forecast, a close, or collections, and the sign-off a person still has to give.
- 02Ship it
We review it with the team each week until people use it every day.
- 03Measure it
Hours, cycle time, and errors against how that job ran before.
- 04Add the next
A second job in revenue or finance, measured the same way.
Case studies
Where we’ve put it to work.
Other services
Seven more ways we put AI to work.
- AI TransformationWe write your AI roadmap, build it, and hand it to your team.
- AI SDLCOne agent-ready flow from idea to merged code, scaled team by team.
- Fine-tuning and EvalsModels tuned to your data, and the evaluations that prove they work.
- ML and Enterprise ForecastingForecasting at enterprise scale, like forecasting Black Friday demand to plan staffing.
- AI Cost OptimizationSeeing where AI spend goes and bringing it down without losing quality.
- Custom Agent and App DevelopmentAgents and AI applications built for one workflow and run in production.
- Context and Knowledge GraphsTurning what your company knows into context your AI systems can use.