Fit
When this is your problem
"Mandate from the top: agents in production this year."
"Our central AI team can't scale to every use case."
"We have a backlog of bot ideas and no way to rank them."
Proof
dLocal ran an agentification program across 9 operations teams, grounded in mapped process truth.
Horizon measured AI maturity in engineering and built the automation agenda from how work actually happens.
Method
How Horizon does it
- 01
Horizon interviews the teams whose work is the automation target, ~25-35 minutes each.
- 02
Horizon ranks agent candidates by hours, feasibility, and risk.
- 03
Horizon delivers an implementation-ready PDD for each candidate.
Outcomes
What you get
- Agent candidates ranked by hours, feasibility, and risk
- An implementation-ready PDD for each candidate
- Works with your builders, ours, or partners
- Grounded in how work actually happens, not slideware
FAQ
Agentification on a process intelligence platform
How do we decide which agents to build first?
Horizon ranks candidates by hours saved, feasibility, and risk, so you build the highest-return, lowest-risk agents first.
Do you build the agents, or just find them?
Horizon delivers an implementation-ready PDD per candidate and works with your builders, ours, or partners.
How is this different from a list of bot ideas?
A backlog of ideas has no ranking or evidence. Horizon grounds each candidate in real work and quantifies the opportunity.
Pick a use case. We'll prove it in a week.
Horizon is an enterprise intelligence platform, a new category of process intelligence, that turns what your people know into evidence, hours, and initiatives.