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AI Agents for Technology

AI Agents for Technology & SaaS Companies

Agentic systems for SaaS platforms, infra companies, and technology organizations — engineered for SOC 2 and ISO 27001 from day one, and for the hard-won realities of running production software.

Technology companies ship the products that other industries depend on, which means their AI deployments carry a second-order responsibility — the agentic patterns they normalize become the patterns everyone else inherits. We build agentic AI for SaaS platforms, infrastructure companies, and internal technology organizations where the engineering bar is already high. Our agents are expected to pass code review, meet SOC 2 and ISO 27001 controls, and operate inside multi-tenant boundaries without surprises. We write the same way we want our clients' engineers to write — small, typed, observable, evaluable.

Where agents earn their keep in technology

Four high-leverage workflows where autonomous reasoning, when bounded correctly, returns real hours back to your team.

Support ticket triage and deflection grounded in product knowledge

Problem
Support teams drown in low-complexity tickets while high-complexity ones sit. Knowledge base and ticket history are separate silos.
Solution
A Support Triage Agent grounded in product docs, runbooks, and past resolutions, drafting responses and escalating what matters.
Outcome
Measurable deflection rate on common questions and faster first-response time on genuinely hard tickets.

Developer copilots for internal platform and SRE teams

Problem
Platform teams repeat the same onboarding, debugging, and incident-runbook walkthroughs across every new engineer.
Solution
A Developer Copilot Agent grounded in internal runbooks, dashboards, and service catalogs, returning answers with links to the authoritative sources.
Outcome
Faster onboarding for new engineers and a documented knowledge graph that keeps working as people rotate.

Incident response and postmortem drafting for SRE

Problem
Incident comms are written by whoever has time during the incident. Postmortems are written by whoever is least tired afterward. Both suffer.
Solution
An Incident Response Agent that drafts stakeholder comms in real time, collates timeline artifacts, and produces a reviewable postmortem draft.
Outcome
Higher-quality incident comms and postmortems that actually ship within SLA.

Revenue-ops intelligence across CRM, product usage, and billing

Problem
Revenue leaders want answers about pipeline, expansion risk, and churn across three systems that don't speak to each other.
Solution
A Revenue Intelligence Agent grounded in the unified warehouse, answering natural-language questions with the SQL it ran and the rows it touched.
Outcome
Self-service revenue answers in seconds, with every figure traceable to a warehouse row.

Agents we deploy in technology

Each agent is a scoped, typed, evaluable piece of software — not a prompt. We ship them behind approval gates and measure them continuously.

Support Triage Agent

Grounded in docs, runbooks, and ticket history; drafts replies and escalates what matters.

Developer Copilot Agent

Answers platform and SRE questions with links to runbooks, dashboards, and service catalogs.

Incident Response Agent

Drafts stakeholder comms during incidents and produces reviewable postmortem drafts.

Revenue Intelligence Agent

Natural-language revenue and usage Q&A grounded in the unified warehouse with full SQL traceability.

Product Feedback Agent

Clusters customer feedback across tickets, calls, and reviews into reviewable themes for PMs.

Looking for the engineering behind these patterns? Read our approach to agentic custom software engineering and autonomous agent design patterns.
Governance

Built for SOC 2, ISO 27001, and multi-tenant isolation

Every technology-company deployment begins with multi-tenant isolation as an architectural commitment — tenant-scoped retrieval, tenant-scoped logs, tenant-scoped evaluation. SOC 2 and ISO 27001 evidence is generated continuously rather than at audit time, and we align with your secure-SDLC practices rather than introducing parallel ones. Where customers are in regulated industries, the agent inherits their controls, not your defaults.

Representative scenarios

How we would approach engagements in technology

Illustrative scoping patterns — not testimonials or client disclosures. Every real engagement is shaped by the customer's data, team, and regulatory posture.

How we would approach support triage for a growing SaaS company

Start with one product surface and the top three ticket categories. Ship the Support Triage Agent behind a human-approved send queue. Instrument deflection and override rates before widening scope.

How we would approach a developer copilot for a platform team

Begin with one service area with strong runbooks. Scope the agent to that area, measure time-to-first-useful-answer for new engineers, and only expand when the platform team requests it.

How we would approach incident response for an SRE organization

Shadow-run the Incident Response Agent on past incidents for two sprints. Compare its draft comms and postmortems against shipped artifacts. Only then integrate with the live incident-management flow.

How we would approach revenue intelligence for a CRO organization

Refuse to begin without a semantic layer over the unified warehouse. Ship a small Revenue Intelligence Agent scoped to five highest-value questions, full SQL transparency, then widen.

Frequently asked

How do you enforce multi-tenant isolation for agents inside a SaaS platform?+

Tenant identity is carried through the entire agent stack — retrieval indexes, tool authorization, logs, and evaluations are all tenant-scoped. We architect for cross-tenant leakage to be impossible, not just unlikely.

Will the agent pass our SOC 2 or ISO 27001 audit?+

Our deployments are designed to produce SOC 2 and ISO 27001 evidence continuously — immutable logs, change management, access reviews, and model-version pinning are built in rather than bolted on.

Can you work inside our existing secure-SDLC and code-review practices?+

Yes — we write the way your engineers expect to review. Small PRs, typed interfaces, tests that run in CI, and evaluation suites committed alongside the code.

How do you evaluate a production agent's quality over time?+

Every release is gated by an evaluation suite with regression, boundary, and adversarial cases. Results are versioned alongside prompts and code so regressions are visible.

Can you help us expose our own agentic capabilities to our customers?+

Yes — that is the core of our Agentic SaaS practice. We design tenant-safe, outcome-oriented agent APIs that integrate with your existing platform surface.

Build your technology agent stack with us

We scope in weeks, not quarters. Tell us the workflow that costs you the most hours and we will come back with a buildable plan.