Engineering · Integration · Governed AI
AI you can put in front of a regulator.
Most organizations can get a model to produce an answer. Far fewer can say what it decided, what it acted on, and who authorized it. RPR builds the layer that makes AI accountable — integrating the systems you already run, automating the work between them, and keeping a record of every decision made along the way.
Service-Disabled Veteran-Owned Small Business · Placerville, California · we build every system we sell
What we do
Five capabilities, one engineering team.
We are not a reseller with a services arm. Every system on this page is one we design, build, deploy and operate ourselves.
AI Governance
Policy enforcement, guardrails, approval gates and an immutable record of every automated decision — built in from the first integration, not bolted on before an audit.
Systems Integration
CRM, ERP, telephony, databases, line-of-business APIs and the legacy systems everyone said could not be connected. Non-invasively: nothing ripped out, nothing rewritten.
Intelligent Automation
The hand-offs that are currently re-keyed by a person, done automatically — with validation, retries, and a complete log of what moved where.
Conversational & Agentic AI
Assistants that answer and agents that act, wired to your live systems, bounded by what you allow, and accountable for what they do.
AI Infrastructure
Dedicated, single-tenant deployments we build, run and extend. Your own environment, your own data, your own keys.
Capability 01 — the one that is usually missing
An AI decision that leaves no trace is a liability, not an asset.
Automated decisions are made and gone in the same instant. When a regulator, an insurer, an auditor or a customer asks what happened and why, most organizations discover they have no answer — only the output. That gap is what we close.
The question arrives before you are ready for it
In our experience it shows up commercially long before anyone cites a statute — in security reviews, in insurance questionnaires, in enterprise procurement, and in board and customer conversations where "how is this governed?" is now something you answer in writing.
Retrofitting an audit trail onto a system that was never designed to keep one is expensive and partial. Building it in from the first integration costs very little and it is the version that actually holds up when someone reads it closely.
Policy at the point of action
What a system may do is declared once and enforced where the action happens — not left to a prompt and good intentions.
Guardrails and blast radius
Every automated actor gets an explicit scope: which systems, which records, which operations, and what it must never touch.
Human-in-the-loop gates
Decisions above a threshold you set stop and wait for a named person. The approval is part of the record, not a side conversation.
Immutable decision records
What was decided, on what input, under which policy, by whose authority, at what time — written append-only and kept queryable.
Data lineage
Every value an automated decision relied on can be traced to the system it came from and the state it was in at the time.
Explainable actions
When somebody asks why the system did that, the answer is a record you can hand them — not a reconstruction.
The test we hold ourselves to: if someone asks what did the system do, why, on whose authority, and on what data — you can answer all four from a record, in minutes, without calling an engineer.
Capability 02
Governance is only possible once the systems actually talk.
You cannot govern what you cannot see. Most of the work of making AI accountable turns out to be integration work — getting the systems of record to agree on what is true, continuously, without replacing any of them.
What you already run
- CRM
- ERP
- Telephony & contact center
- Databases & warehouses
- Line-of-business APIs
- Legacy systems with no API
What it makes possible
- Clean, current, joined data
- Automated workflows
- Assistants and agents that act
- Models fed something worth eating
We connect through official APIs and webhooks where they exist, and build event-driven bridges where they do not — including legacy applications captured without modifying them. No rip-and-replace, no code changes to the system your business runs on.
Capabilities 03 & 04
Once data flows clean, automation is the dividend.
Intelligent automation
The work that is currently a person copying a value from one screen into another is the work we remove first. Not because it is glamorous, but because it is measurable, low-risk, and it compounds: every hand-off automated is a hand-off that stops introducing errors downstream.
Each automation ships with validation, retries, and a complete log of what moved where — so when something does go wrong, you find out from the system rather than from a customer.
Conversational & agentic AI
A standard assistant answers. An agent acts — resolving routine multi-step work end to end. The distinction matters enormously for risk, so we treat it as a governance question first and a capability question second.
Every agent we deploy has an explicit scope, an approval threshold above which a human decides, and a full record of what it did. That is what makes it deployable in a business that has auditors.
Assistants and agents are wired into the same governed path as every other automated actor — no separate, unlogged channel.
Capability 05
Your own environment. Nobody else's data in it. Ever.
Every customer gets a dedicated, single-tenant deployment — its own server, its own databases, its own credentials. We build it, we run it, and we extend it as you grow.
- Dedicated infrastructure per customer — no shared tenancy, no pooled data
- Deployment, monitoring and operation handled by the engineers who built it
- Containerised and modular, so capability is added without redeploying the estate
- Your data stays in your environment and remains yours on exit
Our platform
ddash is the product we built doing this work.
After enough integration projects that all needed the same foundation, we built it once, properly. ddash is RPR's integration, data and governance platform — the substrate most of our engagements run on, and the reason we can start from a working system rather than a blank page.
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Connect
Bridges into the systems you already run, including the ones with no usable API.
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Clean
Deduplicated, normalized and structured continuously — not as a one-time cleanup.
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Govern
Policy, lineage and an append-only record applied to everything that moves.
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Act
Automations and agents operating on data that is current and trustworthy.
ddash is ours — we build it, we run it, and we are the only people who support it. It is a platform, not a license we resell.
How engagements work
Research, Products, Results.
It is what the initials have always stood for — Research → Products → Results — and it is still how the work runs.
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Research
Understand the business before proposing anything.
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Products
Design, integrate, build and deploy the solution.
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Results
Measure the operational outcome.
Platforms we integrate
Environments we have delivered production integrations into — not products we sell. If your stack is not listed, that is not a blocker; it is the first thing we scope.
Communications & contact center
Where the deepest integration work sits.
- Dialpad
- Vonage
- Cisco
- GoTo Connect
- NICE CXone
CRM & ERP
Systems of record we have integrated and extended.
- SuiteCRM
- Epicor
- Odoo
- QuickBase
Data & infrastructure
Where integrated data lands and runs.
- PostgreSQL
- MySQL
- SQL Server
- Containerized Linux
Named platforms are systems RPR integrates with and deploys into. Listing here describes our engineering experience, not a partnership, endorsement or reseller relationship. All marks belong to their respective owners.
Who you would be working with
Builders, not resellers.
RPR Technologies is a software engineering company in Placerville, California, and a Service-Disabled Veteran-Owned Small Business. We build every system we sell, we run every system we deploy, and the people who scope your project are the people who answer your email afterwards.
That is not a service tier. It is the size and shape of the company — small enough that you talk to a decision-maker, established enough to run production systems for customers who cannot afford downtime.
Start with a conversation, not a proposal.
Tell us what you run and what you want it to do. We will tell you honestly what is achievable with the data you have today, and what would have to change first.