Days to resolve support issues.
Reported after combining improved internal procedures with North automation.
Read the customer case study ↗Enterprise AI. On your terms.
Get your team’s time back. Keep control of your AI.
Find the information your people need. Move work past the repetitive steps. Build useful AI into the products your customers already use.
Start with the work you need to improve. You don’t need to choose a model first.
What changed in practice
Improvement in search-result quality.
Reported on DraftWise’s internal benchmarks after incorporating fine-tuned Cohere models.
Read the customer case study ↗These results describe specific customer deployments. They are not forecasts for yours. Measurement context is included in each published case study.
CoreWeave
DraftWise
BambooHR
Atomicwork
Less work around the work
Your people shouldn’t have to assemble the answer before they can do their job.
A customer needs help. The context is spread across tickets, documents and conversations.
Someone needs a policy answer. Your HR team has already answered the same question.
A specialist needs a precedent. Finding it takes attention away from the judgment you hired them to provide.
You need less work around the work. And a way to change it without creating another system your people have to work around.
“There were too many barriers.”
Start with your job
What do you need to get done?
Choose the situation closest to yours. See the relevant product path, the support to discuss and a related customer example.
Your starting path
Make your knowledge easier to use.
Retrieve relevant information across connected sources. Add a workspace when your team also needs to act on what it finds.
- Products to explore
- Compass · North
- Support to discuss
- Source connections, permissions and retrieval evaluation.
- Related customer example
- BambooHR · Embed and Rerank ↗
Not sure where to start? Bring the task that creates the most repeated work. You can change your selection at any point.
Your product paths
Choose what helps you finish the job.
You may need a workspace for your people, a search system for your knowledge, or models for an application you’re building. Start with the relevant capability.
Give your people more time for the work that needs them.
Help your team find information, prepare documents and complete repeatable workflows in an enterprise AI workspace.
Connect supported tools and data sources. Configure multi-step automations with testing, versioning and approval points.
What you’re working toward
Discuss your workflow ↗
Product capabilities ↗
Fewer manual steps between a request and a useful result.
Make your organization’s knowledge usable.
Retrieve relevant information across connected sources, document formats and languages.
Bring document processing, retrieval models and a managed search index together, with document-level security and role-based access controls.
What you’re working toward
Discuss knowledge access ↗
Product capabilities ↗
Answers grounded in the knowledge your organization already has.
Give your customers useful AI inside your product.
Build the experience your customers need without developing every underlying model yourself.
Select generation, retrieval, document-processing and audio capabilities around your application. Evaluate the combination against your own use case.
What you’re working toward
Discuss your application ↗
Explore the models ↗
Useful functionality within the experience your users already know.
- Command ↗
- Generate responses, prepare drafts and support tool-using agents.
- Embed + Rerank ↗
- Retrieve information by meaning and prioritize relevant search results.
- Parse ↗
- Extract usable information from documents, including tables and visual content.
- Transcribe ↗
- Convert recordings into text for search, analysis and downstream workflows.
Working with specialized language or translation needs?
Include those requirements in your conversation. North Small Translate is another offering to explore. Confirm its applicable licensing and commercial-use terms before planning a production deployment.
Your operating boundaries
Your next capability should fit your business.
Choose the deployment arrangement around your data requirements and the responsibilities your team wants to retain. Select an option to include it in your brief.
Know what happens to your data.
For private deployments and third-party cloud AI/ML platforms, Cohere states that it does not receive customer prompts or generations.
Its own SaaS platform has different logging, retention and training-use controls. Confirm the arrangement that applies before connecting sensitive information.
Commercial partner perspective
“…removing the operational burden for our customers.”
Your implementation support
You need a working deployment. Not another project to figure out alone.
Bring your business requirements. Choose the support you need to discuss alongside your product and deployment decisions.
Shape the solution.
Solution architectureConnect your use case, business requirements and infrastructure choices with technical specialists. Start with what the solution must accomplish.
Adapt the model.
Model customizationExplore custom pre-training or post-training, supported by data annotation and Cohere-run model training for specialized use cases.
Put it into operation.
Deployment supportGet technical help tailoring your private deployment, with applied machine-learning support for model accuracy and efficiency.
Keep improving after launch.
Customer success and supportAgree on customer-success involvement, technical support and service-level commitments appropriate to your deployment.
These headings organize the support conversation. Service scope, responsibilities and commitments depend on your agreement. Customization capabilities ↗ · Private-deployment support ↗
“The Cohere team have been incredibly helpful design partners, collaborating closely with us…”
See the whole job
A connected path from request to resolution.
Your workspace, information sources, models and review points should work together around a task. Here is an illustrative support workflow.
Example job
Move a support request toward resolution.
-
Your request arrives.
An automation starts through a connected application.
-
Your context is retrieved.
Configured knowledge sources supply relevant information.
-
A next step is prepared.
The selected model produces a suggestion using that context.
-
Your review happens where required.
The appropriate person checks the proposed action before it continues.
-
The work moves forward.
Connected tools carry out the configured next action.
Products: North Automations, configured retrieval and a selected generation model. Deployment: where your system runs. Support: who helps design, configure and operate it.
Customer outcomes
Look at the work that changed.
Different organizations. Different jobs. Specific examples of what changed after implementation.
90 days
To broad production deployment.
Give your engineers context before they start solving.
CoreWeave embedded North into its Slack-based support process. The case describes less manual context gathering and more time for engineers to solve customer problems.
Read the support story ↗30%
Search-quality improvement on internal benchmarks.
Find relevant precedent, not just more search results.
DraftWise combined Cohere models in its contract-drafting application to retrieve relevant material and generate text with source citations.
Read the application story ↗Tens of thousands
Of employee questions addressed in the published case.
Give employees an answer without another HR request.
BambooHR built Ask BambooHR using company information and access permissions. BambooHR led the product’s design and implementation, with Cohere providing retrieval models and technical guidance.
Read the employee-answer story ↗Selected Cohere-published customer stories. Outcomes depend on the application, available information, implementation and operating process.
In their words
Hear what mattered to the people putting it to work.
Reliability. Infrastructure fit. Collaboration. The details behind the decision, in the words of customers and a co-development partner.
CoreWeave
“For all of the systems we integrate with, it's been a very, very reliable platform”
DraftWise
“Once we knew that we could run Cohere models on Azure, we were sure we’d have the best of both worlds”
RBC
“…the level of flexibility and collaboration that we need…”
Atomicwork
“…even helping tune prompts for very specific use cases…”
Selected published comments, with roles as attributed in those publications. These are not a representative customer-satisfaction survey. Ellipses identify excerpts.
A decision you can stand behind
Make useful progress. Keep the important questions visible.
You need a result for the people doing the work. You also need answers for the people responsible for approving, operating and funding it.
What changes for your business?
Choose a task. Define the result worth paying for and how you will measure it.
What will your technical team need?
Identify the systems, data, integrations and operational responsibilities.
Where are your operating boundaries?
Review access, deployment and data-handling requirements before implementation.
Does it help the people using it?
Test whether the workflow saves effort after checking answers and correcting mistakes.
Before you commit
Your questions deserve clear answers.
Do you have to replace your existing systems?
Explore connections through North’s APIs and built-in connectors, or integrate Cohere models into an application you’re developing. The work required depends on your systems and use case.
Confirm your required integrations during evaluation. Explore North ↗
Do you need the entire product portfolio?
Start with the relevant offering: North for a workforce platform, Compass for enterprise search, or models for an application. Confirm the components and commercial scope in your proposal.
Can you use sensitive company information?
Evaluate the deployment and data controls before doing so. Private deployment, third-party cloud access and Cohere’s SaaS platform do not have identical data-handling arrangements. Your configuration and agreement matter.
Can you inspect and review what the AI produces?
Source-grounded responses and citations can help you inspect an answer. North Automations includes configurable approval steps for workflows. These controls do not eliminate errors or replace the review your use case requires.
How quickly can you see value?
Set that expectation around a defined task. Identify data readiness, integration work, security review and the people needed for evaluation before agreeing to a timeline.
Treat another customer’s implementation time as context, not your delivery commitment.
What will it cost?
North and Compass use custom enterprise pricing. Cohere also publishes model and Model Vault pricing. Costs depend on the offering and deployment.
Ask for a proposal that makes software, infrastructure, implementation and support responsibilities explicit. Review published pricing ↗
Start with one job
Bring the task you need to improve.
See which route fits your business. Use your demo conversation to examine the work, the systems it depends on and the requirements a deployment must meet.
Make the job specific.
Which workflow creates the most repeated work?
Examine the fit.
Which capabilities and deployment boundaries matter?
Define the test.
What would you need to see before moving forward?
Your job. Your requirements. Your next step.
Your selections are gathered below so you can keep the conversation focused.
- Your job
- Find the answer.
- Products to explore
- Compass · North
- Deployment preference
- To be discussed.
- Support to discuss
- To be discussed.
Continue on Cohere’s site to request your demo. Copy your brief to keep these requirements at hand.
Continue to request your demoYour selections on this page are not automatically submitted through this link.
Your request has been received.
Your selected job and requirements were included. Continue exploring a related customer story.
Read the related story ↗Prefer to explore first?
Explore the North interactive demo ↗Your people have work worth doing. Give them less work around it.
Choose the task that needs to change. Find the right capability. Define the controls. Test the result.
Request your demo