Agents for work that does not fit in one prompt.

Most AI handles summaries, lookups, and single tasks. Across is built for the processes that keep going: renewals, product delivery, financial close, and the handoffs around them, with memory, governance, and a person in the loop where it matters.

Our team has built and researched at
UC Berkeley Stanford University Google University of Southern California Oracle Salesforce Yahoo! Meta
The shift

One-shot tasks are solved. The work that moves a business isn't.

Summaries, lookups, single prompts: done. But renewals, the software lifecycle, and the financial close span teams, systems, and time. Across is built for that kind of work.

AI can complete tasks.Across runs processes.

A task ends in seconds. A process runs for weeks, across systems, policies, approvals, and people. It has to hold its context the whole way.

One-off task

Prompt “Summarize the Northwind call”
Output Summary delivered · 7s
No memory. No policy. No next step.

Process record

Order-to-cash process, Invoice #4417

Meridian Health Started Jan 12 Day 47 · Running
Day 9 Credit approved, routed to Finance and signed off
Day 3829 days later Invoice issued, matched to PO 88-231
Day 479 days later Payment overdue, reminder drafted for review

Context carried forward

PO match · payment terms · credit approval · prior exception

Salesforce NetSuite Outlook Human approval Review draft

47 days in and still running.

The work that moves a business runs across systems and changes over time. This is the work Across is built for.

By team

Where teams use Across.

Select a team to see what the agents do.

Finance & operations Payables, reconciliations, and the close, all run end to end.

Agents that understand financial processes handle payables and reconciliations end to end, with full lineage and human review for the exceptions that matter.

See the payables case study
Case AP-A · tax-inclusive invoice PAY
on path reasoned gate not used
Compliance Financial operations an examiner can walk through.

The regulatory context (data lineage, control logic, policy semantics, audit trails) that makes agentic AI defensible inside a regulated bank: KYC onboarding, alert triage, and SAR drafting, each with the evidence attached.

See the compliance case study
Case AML-2 · unusual-activity alert ESCALATE
on path reasoned gate not used
Product & engineering Software delivery, aligned from planning to release.

Agents connect requirements, meetings, Jira, and engineering work. An AI teammate runs standups and follow-through, turning scattered feedback and tickets into traceable, prioritized work.

See the case study
Case ENG-4 · release readiness SHIP
on path reasoned gate not used
GTM Revenue execution that moves every account forward.

Prep renewal and expansion calls with the latest account history, and draft account briefs and follow-ups your reps can send.

“It's like having a strategist embedded in every deal.”
Venkat Nagaswamy, Chief Revenue Officer, Splashtop
See the enterprise proof
Case GTM-9 · renewal window RENEW
on path reasoned gate not used
Why Across

Roughly eighteen months to build what we deploy in weeks.

Durable memory, cascade updates, lineage, and governed action are not features you bolt on at the end. They shape the architecture. Teams that try to build the reasoning layer in-house can spend the better part of two years on it before it reaches production work. Governance (permissions, lineage, and audit) is built into the platform.

Build
~18 months

An eighteen-month detour.

Memory that survives across systems, cascade updates, permissions, and audit trails are deep infrastructure. Building them in-house pulls your best engineers off the product that differentiates you.

Buy
Weeks

Live in weeks, not months.

Across deploys the reasoning layer into your environment in days, not quarters, so teams preserve process state instead of rebuilding plumbing.

It runs headless beneath the agents, models, and systems you already use, so there is no rip-and-replace.

How we work

  1. 01

    Proof of concept

    One real workflow, on your stack.

  2. 02

    Pilot

    A live team, human in the loop.

  3. 03

    Production

    Rolled out under your governance.

Common questions

The questions enterprise teams ask first.

Do you train on our data?
No. Across runs inside your environment and does not train on your data. You own everything the system holds in memory.
Who owns what IP?
You do. The instance of the reasoning graph we deploy for you, your business logic and all the data inside it, is owned by your company. What Across owns is the IP for building, maintaining, and improving reasoning graphs over time, namely the architect agent and the know-how to create one.
Can we use our own models?
Yes. Across runs on the models you approve, and only those.
Can it work with other agents?
Yes. Across exposes its operator agent over MCP (and A2A), so your existing agents can connect and talk to the agents on the platform, and ours can talk to yours. Bringing another agent into the network is as simple as pointing it at an MCP server.
Where does it run?
Your choice. Across can be hosted within your own cloud, containerized under your governance and deployment controls, or hosted in ours. Either way it runs headless beneath the systems your teams already use.
How are permissions and governance handled?
Agents inherit each user's permissions. Permissions, lineage, and audit are part of the architecture, managed on the platform.
Is every action auditable?
Yes. Every agent has its own data lineage, its own history of every transaction that agent has ever done, so you get full data lineage on what it is doing and why. Actions are tagged as agent-originated, and a person signs off on anything sensitive.
Why buy this instead of building it?
Building the reasoning layer in-house takes most teams the better part of two years. Across deploys it in weeks, headless, with nothing to rip out.
How do we get started?
A focused POC on a workflow you choose, then a pilot with a live team, then production across your systems.
Get started

Start with one workflow where context loss is expensive.

Bring Across into one workflow where memory matters, review matters, and the next action cannot be guessed from a single prompt: payables, a sprint team, a book of accounts.

Request demo