What would you like to know?
Clear answers about the two practices, what we build and manage, and the responsibilities around an AI system.
33 questions
Working with Ryzolv
What does Ryzolv do?
Ryzolv is an AI engineering company with two practices. AI Engineering builds custom agents, applications and integrations. Ryzolv Automate sets up, connects and manages business workflows for appropriate smaller businesses.
Which practice should we speak to?
Choose AI Engineering when you need a custom system, application or integration. Choose Ryzolv Automate when you need managed workflows around enquiries, sales, jobs, scheduling, payments and follow-up. If the work spans both, describe the process and we can clarify the scope.
Do you work with startups?
Yes. AI Engineering serves startups, mid-market companies and organisations with complex engineering requirements. The starting point is a defined problem, suitable access to the required information and an accountable process owner.
Where do you work?
Ryzolv works from Ontario and Bucharest, with services available to teams in Canada, the United States and Europe. Collaboration, support hours and data-processing arrangements are agreed for each project.
How do we start a conversation?
Describe the work, the systems involved and what you want to improve through Discuss Your Project. We can then clarify whether AI Engineering, Ryzolv Automate or a combination fits the process.
AI Engineering
What is an AI harness?
An AI harness is the surrounding runtime and controls that let a model perform a defined task within an application. It can manage context, tools, task state, permissions, verification and operating evidence. The responsibilities depend on the workflow.
What is an AI employee?
AI employee is a business description for software carrying out a bounded recurring role. It is not a human worker or an independent professional decision-maker. Define the tasks, system access, review requirements and operating owner explicitly.
When do we need AI rather than ordinary automation?
AI can help interpret varied documents, language or requests. Ordinary automation is often suitable when the next action follows known rules, such as sending a reminder after a confirmed booking. A useful system may combine both.
What is RAG?
Retrieval-augmented generation finds relevant information in external sources and supplies it to a model when answering. A policy assistant, for example, can return an answer with links to the passages it used. Source quality, access and freshness still need testing.
Do we need to fine-tune a model?
Not necessarily. Start with an evaluated baseline. Retrieval can supply changing business knowledge, while fine-tuning can adapt task behaviour using examples. Better parsing, instructions or software validation may solve a problem without additional training.
Can AI perform our calculations?
For our controlled workflows, exact figures should come from a calculation path that can be traced and rerun. AI can help identify or interpret source inputs, while software validates and calculates and the appropriate person reviews consequential decisions.
Can you connect to our existing systems?
Integration depends on the available interfaces, authentication, permissions and the actions required. We establish the system of record, validate requests and define failure handling. We do not assume that every product exposes the connection a proposed workflow needs.
How is an AI harness different from a model or agent framework?
The model generates outputs. An agent framework provides building blocks for an application. The harness is the surrounding runtime and controls for the actual workflow, including tool access, state and verification. A framework can help build it, but the application still needs to enforce its own boundaries.
Ryzolv Automate
Is Ryzolv Automate a CRM?
Customer records are one part of it. Ryzolv Automate connects the agreed workflows around enquiries, sales, jobs, scheduling, payments and follow-up in a managed operations center. We set up the connections and maintain the system with your team.
What do you set up and manage?
The scope can include lead capture, follow-up, bookings and reminders, customer updates, review requests, repeat-work communication and reporting. We define which workflows and connections fit your process, then manage the agreed setup.
What does our team still do?
Your team handles daily work, customer relationships and decisions that need a person. You help explain the process, arrange the required access and review the setup. Ryzolv manages the agreed system and works with you on exceptions and improvements.
Can it connect job activity and payments?
Where the relevant systems provide suitable interfaces and access, job or payment events can feed the agreed workflow. We confirm the actual connection, record ownership and failure handling during setup rather than promising universal compatibility.
Does every automated step use AI?
No. Many reminders, status changes and follow-ups use defined software rules. AI is useful where interpreting language or varied information adds value. Routine actions should not depend on a model when ordinary automation is sufficient.
Who maintains the workflows?
Ryzolv sets up and manages the agreed system. The ongoing scope includes reviewing operation and working on improvements with your team. Responsibilities, available connections and support arrangements are defined for the engagement.
Can we keep our existing CRM and accounting software?
We start with the tools you use today and check their interfaces, access and data. Some can connect directly; others may need a different hand-off. We agree which systems remain and how they connect before configuring the workflow.
What happens to missed calls and after-hours enquiries?
Where the phone and enquiry channels support it, we can configure an acknowledgement, record the request and route the next action. After-hours messages can set expectations for a reply. Staff handle enquiries that need a person; response channels and timing are agreed during setup.
What can the owner see without chasing the team?
The agreed views and reports can show enquiry stages, scheduled work, pending follow-ups and exceptions. Payment information can be included where the accounting connection supports it. We define the useful view with you and the information staff need to keep current.
Security and data
Does our AI have to run on-premise?
Not universally. The right deployment depends on the data, legal and contractual requirements, performance and operating responsibilities. Private hosting, cloud services and approved combinations have different trade-offs; none establishes compliance by itself.
Does PIPEDA require all data to stay in Canada?
PIPEDA does not impose a blanket ban on transferring personal information outside Canada for processing. Organisations remain accountable for appropriate protection. Provincial, sector-specific or contractual requirements may add constraints, so the actual arrangement needs review.
Does RAG guarantee accurate answers?
No. Retrieval may miss a passage, return a stale source or supply information the model misinterprets. Test retrieval and generation separately. Citations support checking but do not prove that every sentence is correct.
Can the model approve its own actions?
In workflows requiring human approval, software must enforce the approval boundary. The model proposes an action; application checks and the authorised person’s decision determine whether it may proceed. A prompt instruction or model confidence score is not equivalent to permission.
What do activity records show?
They can show observable inputs or safe references, configuration, checks, tool requests, outcomes and approvals. They do not reveal a complete causal account of the model’s internal reasoning. Access and retention should reflect the sensitivity and purpose of the records.
Can you guarantee regulatory compliance?
No engineering implementation alone establishes that every applicable obligation has been met. We can help implement and test agreed technical controls. Legal applicability, conformity decisions and regulated professional judgement remain with the accountable organisation and its advisers.
Implementation and support
How is an Engineering project delivered?
We work through requirements, scope, build, verification and operational support. The project defines what the system can do, which actions need approval and what evidence is needed before release. See How We Work for the full method.
How long does implementation take?
Timing depends on scope, access, integration complexity and the evidence required before launch. We establish a delivery plan after reviewing those dependencies rather than publishing a universal timetable.
How do you test an AI system?
We define representative tasks and acceptance criteria, then check model outputs alongside permissions, source handling, tool outcomes, failure paths and review steps appropriate to the scope. Passing those tests supports a bounded release decision; it does not guarantee every future output.
What happens when a connected system fails?
The workflow needs a defined stop, retry, reconciliation or human-review path. A timeout does not prove that an external write failed. We account for uncertain outcomes and duplicate prevention where the target interface permits it.
What happens after launch?
The engagement defines ownership, monitoring, support and change responsibilities. Model, prompt, source and integration updates should be reviewed against relevant tests. Automate includes ongoing management of the agreed workflows.