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Multi-agent SaaS support triage, autonomous onboarding copilots, and agentic AI engineered inside your product's authorisation model — per-tenant retrieval, product-analytics observability, first-class tenant isolation.
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. For SaaS platforms we ship agentic support triage, onboarding copilots, and internal ops agents that live inside the product's existing authorisation model. The stack is LangGraph, per-tenant retrieval, and observability that treats every agent action as a first-class event in the product's own analytics pipeline. Not a bolted-on chatbot.
Four high-leverage workflows where autonomous reasoning, when bounded correctly, returns real hours back to your team.
Each agent is a scoped, typed, evaluable piece of software — not a prompt. We ship them behind approval gates and measure them continuously.
Grounded in docs, runbooks, and ticket history; drafts replies and escalates what matters.
Answers platform and SRE questions with links to runbooks, dashboards, and service catalogs.
Drafts stakeholder comms during incidents and produces reviewable postmortem drafts.
Natural-language revenue and usage Q&A grounded in the unified warehouse with full SQL traceability.
Clusters customer feedback across tickets, calls, and reviews into reviewable themes for PMs.
The multi-agent triage stack for SaaS support. Classifier + retrieval + drafter agents with per-tenant grounding and support-agent review before send.
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.
Illustrative scoping patterns — not testimonials or client disclosures. Every real engagement is shaped by the customer's data, team, and regulatory posture.
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.
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.
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.
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.
Most technology engagements combine one or two of our service lines.
Deep-dives from the Inductivee engineering blog that go deeper on the patterns behind the agents above.
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.
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.
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.
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.
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.
It lives inside the product's authorisation model — per-tenant retrieval, per-user permissions, product analytics as the observability layer, and no separate identity system. A bolted-on chatbot is a different product with different auth; a SaaS-native agent is a feature of the same product.
Per-tenant retrieval indexes, per-tenant API keys where the model provider supports them, and a guardrail that blocks cross-tenant referencing at the prompt level. Tenant isolation is a hard architectural boundary, not a soft prompt instruction — we treat it that way from day one.
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.
