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DataInn Technologies

Agentic AI

Agents built for the work that comes after the demo.

Tool-using, multi-agent and human-gated systems that do real work in your systems — with evidence for each step.
Book a readiness callFind your pattern

Perceive

Read the world

Reason

Plan a step

Act

Call a tool

ap-reconciliation-agentcompleteIllustrative
Tools
3 allowed
Oversight
Human gate
Trace
Retained 7 years
Workflow
Accounts payable
  1. 09:02:11planReconcile supplier statement against open invoices for this period
  2. 09:02:12erp.queryFetched open invoices for supplier · caller's permissions applied
  3. 09:02:14docs.readParsed supplier statement PDF · sources cited
  4. 09:02:17actMatched most lines · flagged items with amount or date mismatches
  5. 09:02:18verifyIndependent verifier: totals reconcile, no duplicate postings
  6. 09:02:18policy.gateAdjustment above threshold → route to named approver
  7. 09:05:40hand-offAP lead reviewed evidence on one screen · approved adjustment
  8. 09:05:41traceRun recorded: inputs, sources, tool calls, model versions, decision
8/8 events

Example run

Plan, act, verify, hand off.

Bounded
The agent can only call granted tools, with schema-valid arguments.
Grounded
Retrieval uses the caller's permissions, and sources are cited.
Checked
A separate verifier confirms invariants before any write.
Accountable
Exceptions go to a named person with evidence attached.

Capabilities

Build, assure, operate.

  • Build

    • Agent and workflow design
    • Tool and MCP server development
    • Access-controlled retrieval pipelines
    • Model routing, fallbacks and fine-tuning

  • Assure

    • Evaluation harnesses and golden sets
    • Red-teaming and prompt-injection defence
    • Policy engines and approval gates
    • Per-run cost and latency budgets
    AI & LLM security

  • Operate

    • Tracing, replay and alerting
    • Drift and regression monitoring
    • Reviewer tooling and queues
    • Fleet governance across workflows

The loop

Perceive, reason, act, govern.

Every agent runs the same four-stage loop, repeating until the goal is met or a person stops it.

01Grounded retrieval

Perceive

Ground the agent in your own systems, not the open internet.

  • Access-controlled RAG pipelines
  • Connectors: ERP, CRM, EHR, data warehouse
  • Retrieval evaluation suites
02Multi-step planning

Reason

Plan multi-step work and choose the right model for each step.

  • Task decomposition
  • Model routing by cost, latency and quality
  • Fallbacks when a step fails
03Typed, scoped, reversible

Act

Call tools and systems through typed, scoped, reversible actions.

  • Schema-checked tool calls
  • Permission-scoped credentials
  • Reversible where possible
04Verify, trace, hand off

Govern

Verify output, trace activity, and hand off to people at key moments.

  • Independent verification before writes
  • Full run traces
  • Named human approvers

Architecture patterns

Four patterns. Pick the simplest one that works.

  • Grounded assistant

    Best for
    Knowledge-heavy questions over your documents and records.
    How it works
    An agent retrieves with the caller's permissions and answers with citations.
    Examples
    Policy Q&A, clinical reference, contract lookup

  • Tool-using agent

    Best for
    Tasks that read and write across several systems.
    How it works
    The agent calls scoped tools; a verifier checks invariants before any write.
    Examples
    Invoice reconciliation, ticket triage, onboarding

  • Multi-agent workflow

    Best for
    Work that benefits from specialists: research, draft, review, ship.
    How it works
    An orchestrator coordinates researcher, writer and reviewer roles, ending in approve or reject.
    Examples
    Diligence packs, proposal drafting, report generation

  • Human-gated automation

    Best for
    High-stakes decisions that need a named approver.
    How it works
    The agent prepares a proposal with evidence; a named person approves or rejects before anything executes.
    Examples
    Credit decisions, clinical flags, payments over a threshold

Safety commitments

Six commitments in every agent we ship.

  • 01

    Every action is a typed tool

    No raw database or shell access. Each capability is schema-checked, permission-scoped and reversible where possible.

  • 02

    Evaluation before launch, regression after

    Tests are built with domain experts and run in CI on every prompt, tool or model change.

  • 03

    Humans at named moments

    Approval gates are part of the design. Reviewers see reasoning, evidence and the proposed action on one screen.

  • 04

    Traces for audit

    Each run records inputs, sources, tool calls, model versions and decisions. Retention follows your data policy.

  • 05

    Runs where your data lives

    Your VPC, your tenancy, or on-prem k3s. Secrets stay out of prompts, and model providers can be swapped.

  • 06

    Code and knowledge stay with you

    Source lives in your repositories and runbooks in your wiki — no lock-in to DataInn or a model vendor.

Scoping quiz

Which pattern fits your workflow?

Four questions. The recommendation is a starting point, not a quote.
Question 1 / 4
Does the task need to change anything in a system, or only answer questions?

45-minute readiness call

Bring one workflow. Leave with a pattern and a plan.

From our offices in Toronto and Dubai.

Book a readiness call
Applied AI services