Welcome to Tsen'awt
Document and information management, office suite, and AI workspace for First Nations and Indigenous organizations, with automated information management, streamlined funding and reporting workflows, and resolutions and governance tracking, deployed on cloud infrastructure you own and govern.
Llama
The platform
Context-aware documents. Clean data. Streamlined workflows.
The order is deliberate. Reporting is only as good as the records underneath it, and inference over a disordered corpus produces confident nonsense.
Migrate or integrate
Move what should move. Connect what stays.
Some records belong on the appliance. Some systems belong where they already are, connected to it. You decide which is which, department by department, and nothing has to change all at once.
Migrate records from your current provider
Integrate the systems you are keeping
Single sign-on and role-based access
The value
What it saves.
Estimates from our own deployment work, and marked as estimates. The rest are not.
Time to find a record
Less time spent locating a record, estimated. One permissioned search across documents, files, scanned text, tasks and notes, instead of a shared drive, an inbox and a filing cabinet.
Records on premises
Storage, database, search, character recognition, conversion and inference all run on the appliance in your own building. Nothing leaves your network to be processed or indexed. Not an estimate.
Weeks to a running system
From discovery to an appliance in the building with your historic record indexed and searchable. Staged, and priced at each stage. Estimated from our own deployments.
Lower total cost at scale
Lower five year cost once your historic record is in the system, modelled at 40 TB against published list prices. Cloud meters storage and inference permanently. The appliance is bought once.
How it works
How a deployment runs.
Staged, and priced at each stage. Every step produces something you keep whether or not you carry on to the next one.
Discovery
Forty hours, department by department, mapping how information actually moves. You keep the map whether or not you go further.
Architecture
Eighty hours turning the map into a record taxonomy, retention rules and a permission model your staff will actually follow.
Deployment
One department first. The appliance goes into your building, records migrate, staff are trained. Managed operations pick up from there.
Plans
What it costs.
Published so you can budget before you speak to anyone. Seats are per user per month. Hardware and setup are quoted separately and listed below.
FAQs
Questions we get asked.
If the answer you need is not here, ask us directly. We would rather answer it once, properly.
What is the EdgePod, and how does an on-premises appliance replace cloud storage?
The EdgePod is a single self-contained appliance that sits in your building, in Canada, and holds the whole system in place of a cloud provider: storage, the database, search indexing, character recognition, thumbnail and preview generation, document conversion, model inference and the rules engine. The request path is deliberately short, web server to application runtime to database to file store, and slower work runs in the background through a job queue, so a long indexing run does not hold up someone opening a file. It is quoted per deployment and sized against corpus volume, growth rate, user count and whether bulk digitisation is in scope. Pricing is on the plans page.
How does automatic document tagging and records classification work?
What office and productivity tools are included, and how do they share one record?
How does on-premises AI work without sending records to the cloud?
How does the platform support OCAP and Indigenous data sovereignty in practice?
Can we keep Microsoft 365 and the systems we already run during migration?
How long does deployment take, and what do managed services cover?
Blog
Notes from the work
Occasional writing on records, reporting, and what sovereignty means once it has to run on hardware someone maintains.
