In-product copilots and agents
Assistants that take real actions in your app through your APIs, with permissions and audit logs.
SaaS & Technology
AI for software companies and digital platforms.
We help product teams ship AI features customers pay for, and help operators run the business on better data: from copilots inside your app to churn prediction and support automation.
Eval pass rate0%
Tickets resolved0
Latency p95--
The challenge
What is holding software companies back.
01
Customers expect AI in the product
Competitors are shipping copilots and agents, and a thin chatbot wrapper will not cut it.
02
Demos are easy, production is hard
Quality, latency, cost and security all fall apart when a prototype meets real users.
03
Support costs scale with growth
Every new customer adds tickets, and hiring support staff eats into margins.
04
Revenue signals hidden in usage data
Product events, billing and CRM live apart, so churn and expansion surprise you.
Where AI pays off
Use cases we build and run.
Each one is scoped to a measurable business outcome and shipped to production, not left as a proof of concept.
LLM evaluation and guardrails
Offline and online evals, red-teaming and guardrails so quality is measured on every release.
Support automation
Agents that resolve tickets using your docs and account data, escalating with full context.
Churn and expansion prediction
Health scores from product usage, billing and support that tell CS teams where to act.
Semantic search and RAG
Search across your product's content that understands meaning, not just keywords.
AI cost and latency optimisation
Model routing, caching and distillation that cut inference bills without hurting quality.
Our approach
How we deliver in SaaS & Technology.
The same disciplined loop we use everywhere, adapted to the data, risks and rhythms of your industry.
Built responsibly
- SOC 2 and ISO 27001 aligned controls
- Tenant isolation and data residency
- GDPR and DPDP data processing terms
- Prompt injection and data-leakage testing
Typical stack
01
Weeks 1 to 2
Product discovery
We start from user jobs and willingness to pay, not from a model.
- User research and workflow mapping with your PMs
- Data, API and permissions audit
- Feature bets ranked on customer value and build effort
02
Weeks 2 to 3
Design and evals first
We define what good looks like before writing prompts.
- Evaluation datasets and scoring rubrics
- Architecture for latency, cost, multi-tenancy and security
- UX patterns for trust: citations, previews and undo
03
Weeks 3 to 8
Build with your engineers
Pair-programmed with your team, in your repo, behind feature flags.
- Weekly releases to internal users, then beta cohorts
- Eval dashboards tracked on every pull request
- Observability for traces, cost and failures
04
Ongoing
Launch and optimise
General availability, then continuous improvement.
- Online A/B tests and quality monitoring
- Cost optimisation through routing and caching
- Knowledge transfer so your team owns it
Case studies
Results from the field.
Case study 01
B2B workflow SaaS
An in-app agent customers actually use
The challenge
An early chatbot answered generic questions but could not do anything, and usage dropped off after the first week.
What we did
We rebuilt it as an agent that calls the product's own APIs to create, update and report on records, with an eval suite running in CI.
Results
41%of weekly active users engage with the agent
92%eval pass rate on release
60%lower cost per request
Case study 02
Vertical SaaS platform
Support that scales without new hires
The challenge
Ticket volume grew faster than revenue, and first-response times slipped past SLA.
What we did
A support agent grounded in docs, release notes and account data now resolves common tickets and drafts replies for the rest.
Results
48%of tickets resolved end to end
70%faster first response
Case study 03
Developer tools company
Seeing churn before it happens
The challenge
Customer success learned about churn at renewal time, when it was too late to act.
What we did
We unified product telemetry, billing and CRM, trained a health-score model and pushed daily risk alerts into Slack and the CRM.
Results
23%reduction in logo churn
3xmore expansion opportunities flagged
Case studies illustrate the kind of engagements we run. Details are generalised and figures are indicative, not guarantees of results.
Other industries
Explore more of our work.
Financial Services
Credit risk, fraud detection, KYC automation and AI-assisted operations.
Retail & D2C
Demand forecasting, personalisation, pricing and catalogue intelligence.
Healthcare & Life Sciences
Clinical documentation, claims processing and patient-journey analytics.
Manufacturing & Supply Chain
Predictive maintenance, quality inspection and inventory optimisation.
HR & Talent
Screening, matching, workforce planning and people analytics at scale.
Let's talk about SaaS & Technology.
Tell us where you are. We will come back within one business day with a point of view, not a sales deck.