AI-native software for the work humans still own.
Agents propose. Your people approve. Every decision logged, every override one click away. EntityNext builds AI-native systems for enterprises that need control alongside speed.
Three things, done deeply.
We resist the urge to be everything to everyone. We do AI systems, the human-in-the-loop software around them, and the durable enterprise platforms that hold them up.
AI systems & agents
Specialist agents trained on your business and your data. Built to ship to production, not impress in a demo.
- Answers grounded in your content
- Multi-step work, not one-shot prompts
- Quality measured before each release
Human-in-the-loop workflows
AI proposes, your people approve. Operational software with the right level of friction in the right places — never the wrong ones.
- Clean approval queues, not noise
- Auto-pass the easy 90%
- Every action logged for audit
Custom enterprise software
Durable web and mobile platforms that hold your business up. Built to outlast the next architecture fad.
- Connects what you already have
- Web and mobile, one system
- Runs in your cloud, on your terms
Where we work.
Operational depth in sectors where AI lands close to the P&L — not the slide deck.
Built by people who ship.
A lot of AI work stops at the demo. We ship agents into production and stay on for the harder part — making them work alongside your people, at audit-grade, on the workflows your business actually runs on.
AI with guardrails
Measured from day one. We don't ship agents we can't evaluate against your own golden cases.
Outcomes, not deliverables
Milestones tied to business metrics. Pilots have a kill criterion before kickoff.
Production in weeks, not quarters
First agent live by week six — measured, signed off, and earning its keep. No slide-deck demos.
Engineers, not account managers
The engineer in the demo writes the code. Founders work the hard accounts.
What the people running it say.
Anonymized by request. Named references available under NDA on request.
“Their human-in-the-loop design was the difference. Finance was actually willing to sign off on agents going into the workflow — that has not been our experience with other vendors.”
“Agents drafted, approvers approved, audit logged every step. Cycle time dropped, headcount didn’t, control got tighter.”
What buyers usually want to know.
Where does our data live?
Customer choice: your cloud, ours (AWS or Azure), or single-tenant. Data residency defaults to your region. Production data never leaves the agreed boundary; embeddings, prompts, and audit logs are scoped to the same residency.
Who owns the IP?
You do. All custom code, prompts, fine-tuned weights, and data pipelines built in the engagement are assigned to the customer. Our internal evaluation frameworks remain ours and are licensed for use within the engagement.
How do you evaluate AI quality?
We build a customer-specific evaluation set during Discovery — golden examples, edge cases, and the metrics that matter to your team. Every release is scored against it, and any regression blocks the deploy. Real production traffic feeds back into the set so quality compounds over time.
How fast can we get to production?
Discovery in two weeks, architecture and evals in three, first agent in production by week six. We don’t do proof-of-concepts that don’t ship.
Tell us what your team is trying to ship.
A few lines on the operational problem, your current stack, and rough timing. We’ll reply with a sharp first take, not a brochure.
- 01A partner reads your brief and replies with a sharp first take — not a generic deck.
- 02If we’re a fit, a 30-minute call to pressure-test the problem on a real call, not a sales pitch.
- 03A short proposal with scope, kill criterion, and a path to first agent live.
Send us a brief
A few lines on the problem is more useful than a polished spec.