AI features your customers use, and internal tools your engineers trust.
We help software companies add AI capabilities to their products and operations — from in-app assistants and search to support automation and engineering workflows — with the evaluation, cost control and release discipline a production product needs.
- In-app help assistant
- Semantic search across customer data
- Ticket triage and drafting
- Code review and test support
Workflows we work on
- 01
In-product AI features
An assistant, smart search or generated summary is designed as part of the product, with tenant isolation, per-customer permissions, usage metering and evaluation built into the release process.
- 02
Support and success operations
Tickets are classified, answered from documentation and account context where confidence is high, and routed to the right specialist with a summary when it is not. Recurring issues are surfaced to product teams.
- 03
Engineering productivity
Internal tools help engineers review changes, write tests, answer questions about the codebase and triage incidents, integrated with the repositories and tooling the team already uses.
Constraints we design for
Multi-tenant data isolation
One customer's data must never inform another customer's answer. Retrieval, caching and logging are partitioned by tenant from the start.
Unit economics
Model and infrastructure costs are tracked per feature and per customer, so pricing and plan limits can be set with real numbers.
Release and regression control
Prompt, model and retrieval changes go through automated evaluation in CI, with the ability to roll back like any other release.
Customer trust commitments
Your security questionnaires and data processing terms shape what providers and regions can be used. We design to your commitments, not around them.
Use cases we can explore
Where we start
Discovery begins with a few direct questions about your operation.
- 01Which customer problem should the AI feature solve, and how will you know it did?
- 02What does a customer's data boundary look like in your architecture today?
- 03What cost per active user can the feature carry at your current pricing?
- 04How are releases tested and rolled back now?
Relevant solutions and services
- Software Engineering CopilotHelp developers understand the codebase, write tests and prepare changes, with every change going through your normal review and security gates.
- Customer Support AgentsResolve routine customer inquiries from your policies and live account data, taking approved actions and handing everything else to your team.
- Enterprise Knowledge AssistantAnswer staff questions from your own policies, procedures and records, with sources shown and access rules respected.
- AI App DevelopmentComplete AI products — interface, model layer, application code and integrations — designed for the people who will use them every day.
- SaaS DevelopmentMulti-tenant SaaS products designed for onboarding, billing, scale and continuous iteration.
- MLOps & LLMOpsEvaluation, release, monitoring and cost control for predictive models and LLM applications once they are in production.
- Generative AI & LLM DevelopmentApplications built on large language models that are grounded in your data, tested against real cases and costed before launch.
Questions buyers ask
Yes. We can deliver a feature end to end or work alongside your engineers in your repositories and processes. See Dedicated Teams.
Tell us the workflow you want to improve.
Tell us about the workflow or product. We reply with questions, a suggested first step and who would work on it.