Data automation & AI orchestration for regulated industries
We build automation around your use case, combining rules, deterministic tools, applied AI and generative AI, so every output is predictable, explainable and auditable. Proven on your data in weeks, run in production on Sorgi, inside your cloud.
Built for the likes of
Regulated · Audited · Safety-critical
The real problem
Proofs of concept are built in a vendor sandbox on copied data. When they work, they have to be rebuilt to go live, and most never are.
Grid models, customer records and account data can't be shipped to someone else's cloud. Most AI tools assume they can.
Generative AI on its own is probabilistic. Engineers, auditors and regulators need the same input to give the same output, with a reason they can check. A model alone can't be the system of record.
Models drift, rules change and data shifts. Without someone running the automation, accuracy quietly decays until people stop trusting it.
Our answer
Build around the use case, not the model. We use rules and deterministic tools wherever the answer must be exact, and AI only where it adds something, all orchestrated on Sorgi from the first prototype to company-wide scale. The prototype you approve is the system that ships, and it never leaves your cloud.
How we build
Ingest, transform, reconcile and move data between systems on a schedule or trigger. No AI where none is needed.
Your business rules, thresholds, standards and regulations, encoded explicitly. Every output passes them before it is released.
Calculations, lookups, system updates and simulations run as code, so the same input always gives the same result.
Trained models for classification, forecasting and anomaly detection, where patterns matter more than fixed rules.
Reading documents, diagrams and messages, drafting and explaining. Used where language is the problem, and checked by rules before anything goes out.
Example · Preliminary power flow study
Read the single-line diagram
Build the network case
Run the power flow
Flag limit violations
Engineer approves
One generative step. Everything that decides the answer is deterministic, and a person signs off.
Use cases
Engineer
What's the rating on feeder 12-F4 past the Elm St recloser?
Agent
336 ACSR, rated 530 A summer normal. Source: network model, segment F4-118.
Utilities · Electric distribution
A voice agent that sits on top of the distribution digital twin, so engineers in the field and in the office can ask the network a question and hear the answer, with the source it came from.
Utilities · Distribution engineering
Assistants that create, read, update and populate technical specifications for distribution engineers, from the utility's standards and the project's own data.
Utilities · Grid planning
A workflow that reads a single-line diagram, builds the study case, runs a static power flow in the cloud and returns a preliminary result for an engineer to review.
Financial Services · Banking operations
An agent that categorizes transactions, analyses patterns across accounts and periods, and hands analysts a short list of exceptions instead of a full ledger.
Financial Services · Trade finance
An agentic workflow that reads trade finance documents, extracts the terms, cross-checks every document in the package and hands a checker a list of discrepancies.
Financial Services · Compliance
Agents that check operational records against regulatory and internal policy rules on an ongoing basis and draft the report a compliance officer signs.
How we work
Stage 1
Process mapping & value · 1 to 4 weeks
We map the value chain, find where time and money are actually lost, and stand up a working prototype of the highest-value use case on your own data.
You leave with
On Sorgi: Discovery workspace
How it worksStage 2
Individual productivity · 2 to 6 weeks
One high-value task automated end to end, combining rules, deterministic tools and AI as the task needs, with a person approving the work where it matters.
You leave with
On Sorgi: Production runtime
How it worksStage 3
Team-wide productivity · 4 to 16 weeks
Data and agentic orchestration across a full business workflow: pipelines, rules, deterministic tools and agents working together, with human approvals at the steps that carry risk.
You leave with
On Sorgi: Workflow orchestration
How it worksStage 4
Company-wide transformation · Multi-year
Multiple workflows and agent teams on one connected platform: an automation and agent factory your organization owns and runs.
You leave with
On Sorgi: Enterprise AI operating system
How it worksThe product inside the service
Sorgi is Dviz's AI operating system. It activates the intelligence already inside your data without moving a single record. We use it to discover, prototype, build, orchestrate and run everything we deliver, from data pipelines and rule checks to agents, so nothing is rebuilt between stages and nothing leaves your control.
Industries
Where we work today · Utilities
Where we work today · Financial Services
Your industry?
Diagnostic
Pick the sentence that sounds most like your organization. We'll tell you where we'd start.
You're saying
“We've prioritized a few specific use cases.”
Where to start
Start with Stage 2. Pick the highest-value use case and we put one automation into production in 2 to 6 weeks, fixed scope and fixed price.
Stage 2: Build Agents · 2 to 6 weeksOn the record
24/7
on-demand support for distribution engineers, answered by voice from the utility's own network model.
Digital Twin Voice AssistantUtilities · Build Agents
Every field
of a technical specification drafted by an assistant, then reviewed and signed off by the engineer who owns it.
AI-Assisted Spec GenerationUtilities · Build Agents
1 upload
of a single-line diagram is all it takes to trigger a cloud-based static power flow study for preliminary analysis.
Automated Power Flow AnalysisUtilities · Develop Agentic Workflows
A backlog nobody can clear, a pilot that never left the lab, a process that only three people understand. Tell us what it is, and we'll tell you honestly whether AI is the answer.
