AI features that fit your product. Delivery that fits your team.
Help product teams add useful AI, search, analytics and integrations to existing software platforms.
Solutions for organizations and teams working across technology & saas.
Integrate useful features into your product and tenant model.
Explore relevant solutionsModernize applications and connect existing product capabilities.
Explore relevant solutionsValidate features around user needs and measurable acceptance criteria.
Explore relevant solutionsBuild focused product increments with practical architecture and handover.
Explore relevant solutionsIllustrative solution areas; scope, applicability and acceptance criteria are validated during discovery.
Add a focused model-backed feature to an existing product workflow.
Typical inputs: User journey, permitted context and model requirements.
Practical output: An evaluated feature with fallbacks and usage controls.
Retrieve approved product or customer knowledge with tenant-aware access.
Typical inputs: Curated sources, permissions and evaluation questions.
Practical output: Source-backed responses with escalation and feedback.
Build retrieval around product records, documents and relevance requirements.
Typical inputs: Permitted records and representative search tasks.
Practical output: A tested search experience with controllable relevance.
Connect agreed events and definitions to answer product questions.
Typical inputs: Permitted usage events and metric definitions.
Practical output: A documented analytics model and dashboards.
Improve a defined part of the product architecture or experience.
Typical inputs: Existing code, constraints and agreed target behavior.
Practical output: A tested increment with migration and rollback notes.
Connect product interfaces and delivery environments with operational controls.
Typical inputs: API contracts, infrastructure constraints and deployment requirements.
Practical output: Documented integrations and monitored delivery pipelines.
Bring your systems, data and teams together with applications, useful AI assistance and clear human responsibility.
Product APIs & events
Approved knowledge sources
Tenant & identity context
Approved connectivity
Data mappings
Source traceability
Work queues & portals
Reporting & search
Reviewable drafts
Authorized teams
Specialist review
Approvals & decisions
Illustrative workflows using synthetic information, not completed client projects.
A user asks a product question, retrieval applies their permissions and a draft answer cites authorized source material.
Discuss this workflowA feature is evaluated against a baseline, released to an agreed cohort and monitored with rollback controls.
Discuss this workflowControls and deployment choices are scoped to your environment and intended use.
Tenant isolation, permission-aware context and appropriate data handling.
Task-based evaluations, fallback behavior and review of generated outputs.
Latency, usage cost, release controls and ownership agreed with your product team.
Illustrative features need evaluation in your product context. Model output quality, latency and cost vary; no universal accuracy or business-growth guarantee is implied.
Examples of technologies discussed for these workflows. Final selection depends on existing systems, access, licensing and evaluation.
Technology marks identify products only; they do not imply partnerships, certifications or endorsement. Specialist industry standards and platforms are assessed individually rather than assumed compatible.
A collaborative delivery approach with concrete outputs.
Understand the workflow, users, systems, constraints and acceptance criteria.
Output: Agreed project scopeDefine interfaces, permissions and a prototype for the key user journey.
Output: Solution prototypeImplement, test and validate the agreed workflow with your team.
Output: Tested working incrementDeploy with handover, monitoring and the agreed improvement plan.
Output: Deployment & handoverEnd-to-end services to support the agreed roadmap.
Answers about starting a technology & saas software, data or AI project.
Yes, where the workflow, data access and product architecture support the use case. Discovery assesses tenant boundaries, identity, interfaces, latency and cost before agreeing a feature scope.
We define representative questions, approved sources and expected behavior, including unavailable information and restricted content. Evaluation checks retrieval, answer support, permission boundaries and escalation.
A focused integration or modernization increment may be sufficient. We assess the existing product and recommend changes according to the agreed use case and constraints.
The engagement can define shared delivery practices, API contracts, code review and handover. Dedicated development options are linked below for teams needing ongoing capacity.
The agreement defines source-code ownership and third-party licensing. Model-provider charges, hosting and operational support are identified as separate assumptions or costs in the proposal.
Tell us about your users, systems and priorities.
